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ОБРАЗОВАТЕЛЬНАЯ ПРОГРАММА 2012/13

STRELKA

EDUCATION PROGRAMME 2012/13

RESEARCH REPORT (RE)CHARGE INFORMATION. HOW TO DEBRIEF THE CITY?


ДИРЕКТОРА Феликс Мадразо, Роберт Буд ПРЕПОДАВАТЕЛЬ Даша Парамонова СТУДЕНТЫ Гульназ Аксенова, архитектор, Уфа; Сергей Касич, экспериментальный музыкант, Севастополь; Тимоти Мисир, политолог, Сингапур; Глафира Паринос, географ, Москва; Мария Ромакина, журналист, Москва; Артур Шахбазян, архитектор, Москва; Катерина Эксамилиоту, архитектор, Салоники, Греция; Оксана Яценко, переводчик и менеджер по коммуникациям, Вологда ЭКСПЕРТЫ-КОНСУЛЬТАНТЫ Маргарита Ангелидоу, Университет Аристотеля в Салониках, Alpha Kapa Meletitiki E.E.; Олег Баевский, Институт Генплана; Мара Балестрини, Университетский колледж Лондона; Эндрю Бата, Бюро стратегических инноваций и технологий; Иван Бегтин, основатель и директор НГО «Информационная культура»; Казис Варнелис, Network Architecture Lab, Колумбийский университет; Ольга Вендина, Институт географии, РАН; Вадим Волович, Метрогипротранс; Людмила Воропай, арт-критик; Кен Голдберг, Центр новых медиа, Калифорнийский университет в Беркли; Мэтью Драйхерст, Фонд поддержки искусства Grey Area (GAFFTA); Оксана Запорожец, антрополог; Филипп Кац, РИА Новости; Джеф Круз, программист и преподаватель, Новая школа дизайна Парсонс; Игорь Крылов, программист; Кристина Кубиш, саунд-артист; Екатерина Ларина, архитектор; Колин Макартур, Школа информации; Джордж Маккеррон, проект Mappiness, Университет Сассекса; Таня Мамаева, Robert Bosch LLC; Амид Морандгандже, IDEO; Илья Мукосей, архитектор; Мор Нааман и Раз Шварц, Школа коммуникаций и информации, Ратгерский университет; Алексей Новиков,

ThomsonReuters; Алексей Новичков, РИА Новости; Кристиан Нолд, Бартлетт, Университетский колледж Лондона; Оливер О’Брайан, исследователь, Центр продвинутого пространственного анализа, Университетский колледж Лондона; Эрик Паулос, Центр новых медиа, Калифорнийский университет в Беркли; Мишель Провоост, Crimson Architectural Historians, Институт новых городов; Кирилл Пузанов, географический факультет, МГУ; Бен Сервени, советник, Flickr; Екатерина Серова, ThomsonReuters, Мосгорчат; Анна Сиприкова, Министерство культуры РФ; Леонор Скенази, журналист; Фелисити Скотт, профессор архитектуры, Высшая школа архитектуры, Колумбийский университет; Майя Стравинская, РИА Новости; Юха ван ‘тЗелфде и Мауритис де Брюйн, журанлисты и разработчики, Shippr; Даша Уткина, Город друг; Мюррей Фешбах, Центр Вудро Вильсона; Адриан Фрид, Центр новой музыки и аудио технологий, Калифорнийский университет в Беркли; Майкл Холланд, Центр урбанистики и прогресса, Нью-Йоркский университет; Сергей Чернов, Центр изучения Интернета и общества, РЭШ; Павел Шорох, РИА Новости


DIRECTORS Felix Madrazo, Robert Bood TUTOR Dasha Paramonova STUDENTS Gulnaz Aksenova, architect, Ufa; Katerina Examiliotou, architect, Thessaloniki, Greece; Sergey Kasich, sound-n-media artist, Sevastopol; Timothy Misir, political analyst, Singapore; Glafira Parinos, geographer, Moscow; Maria Romakina, journalist and artcritic, Moscow; Artur Shakhbazyan, architect, Moscow; Oxana Yatsenko, interpreter and communications manager, Vologda EXTERNAL EXPERTS Margarita Angelidou, Faculty of Architecture, AUTH, Alpha Kapa Meletitiki E.E.; Oleg Baevskiy, Institute of Genplan; Mara Balestrini, University College London; Andrew Bata, Office of Strategic Innovation and Technology; Ivan Begtin, founder and director of NGO Information Culture; Ben Cerveny, advisor & founder, Flickr; Sergey Chernov, Center for Internet and Society, New School of Economics; Jeff Crouse, Parsons the New School for Design; Matthew Dryhurst, Grey Area Foundation for the Arts; Murray Feshbach, Senior Scholar, Woodrow Wilson Center; Adrean Freed, Berkeley Center for New Music and Audio Technologies; Ken Goldberg, Berkeley Center for New Media; Michael Holland, NYU Center for Urban Science & Progress; Philipp Kats, RIA Novosti; Christina Kubisch, sound artist; Ekaterina Larina, architect; Geert Lovink, founding director, Institute of Network Cultures; Tanya Mamaeva, Strelka alumni, Robert Bosch LLC; Сolin MacArthur, School of Information; George McKerron, Mappiness project, University of Sussex; Amid Moradganjeh, IDEO; Ilya Mukosey, architect; Mor Naaman & Raz Schwartz, School of Communication

and Information, Rutgers University; Christian Nold, Bartlett, University College London; Aleksey Novichkov, RIA Novosti; Alexey Novikov, ThomsonReuters; Oliver O'Brien, Research Associate, Centre for Advanced Spatial Analysis, University College London; Eric Paulos, Berkeley Center for New Media; Michelle Provoost, Crimson Architectural Historians, New Town Institute; Kirill Puzanov, Faculty of Geography, MSU; Ekaterina Serova, ThomsonReuters, Mosgorchat; Pavel Shorokh, RIA Novosti; Anna Siprikova, Strelka alumni, Ministry of Culture; Leonore Skenazy, journalist; Felicity Scott, Associate Professor of Architecture, Graduate School of Architecture, Planning and Preservation, Columbia University; Maya Stravinskaya, RIA Novosti; Dasha Utkina, Gorod Drug; Kazys Varnelis, Network Architecture Lab, Columbia University; Olga Vendina, Institute of Geography, Russian Academy of Science; Vadim Volovich, Metrogiprotrans; Ludmila Voropay, art-critic; Juha van 't Zelfde & Maurits de Bruijn, data journalists and developers of Shippr; Igor Krylov, software architect; Oxana Zaporozhets, anthropologist


(ПЕРЕ)ОСМЫСЛЕНИЕ ИНФОРМАЦИИ: КАК ПРАВИЛЬНО «ЧИТАТЬ» ГОРОД? В последние годы объем данных, производимых цифровыми устройствами, растет в геометрической прогрессии. Социальные сети, мобильные телефоны, камеры, сенсоры и т.п. производят бесконечный поток сообщений, сигналов, фотографий. Ежедневно мы создаем миллионы миллионов бит информации. С каждым днем количество новых пользователей увеличивается, а вместе с этим растет объем данных. Эпицентрами, где рождается этот поток информации, становятся города. С одной стороны, это мощный толчок к их развитию, с другой — новые сложности и дилеммы. Создание концепции «умного города» — многообещающе и перспективно, но воплотить ее в жизнь не так просто. Вопрос в том, кому принадлежат эти данные и кто их контролирует. Если правительства разных стран открывают доступ к своим базам данных, то позиция коммерческих компаний, к которым информация стекается в реальном времени и потому является более ценной, куда менее очевидна. Участники студии исследовали, как производятся и используются данные и как они влияют на развитие городов, в частности Москвы. Один из самых крупных городов в мире, Москва может стать чем-то вроде лаборатории по изучению данных и их влиянию на окружающее пространство. Исторически сложилось так, что монополия на информацию в России принадлежит государству. Поэтому содержание блогов, которые ведут пользователи самых разных социальных сетей, полностью меняет перспективы развития города: чиновникам все сложнее игнорировать мнение горожан о качестве окружающей среды и принимаемых мерах. В течение учебного года студия провела множество встреч с самыми разными экспертами из разных стран: чиновниками, активистами, бизнесменами. Одни относятся к понятию «данные» и их значению в эру цифровых технологий скептически. Другие, наоборот, превозносят удивительный потенциал этих данных. Чтобы как следует узнать эти полярные точки зрения, студия отправилась в две исследовательские поездки: в Берлин,


(RE)CHARGE INFORMATION: HOW TO DEBRIEF THE CITY? The explosive growth of data in recent years is beyond imagination. Social media, mobile devices, cameras and sensors generate a never ending flow of messages, signals, pictures and log files. Together, we create an astonishing 2.5 quintillion (that is: a billion billion) bytes of data every day. As a result, ninety percent of all data in the world has been created in the past two years. With new users and smarter devices added all the time, the flow of data will only grow in the years to come. ‘Big data’ is here to stay. Cities are clearly the epicenters of the data generation, offering rich potential for city development but also presenting some critical challenges and dilemmas. The search for creating smart cities is intensive and promising in many respects. Analyzing and using it is, however, far from easy and more than just a methodological challenge. Moreover, do we want to have instantaneous insight into everything and all the time? It leads directly to the question who owns and controls data. Governments all around the world open up their databases for everyone to use. It is less clear-cut for the owners of the most valuable real-time data sources that come from the commercial sector.  The studio set out to research the way digital information is generated and used, and explore its potential for developing cities, Moscow in particular. Being one of the largest cities in the world, Moscow presents a magnificent laboratory for exploring the influence of digital data. With a history of government monopoly of information, the availability of user-generated data from all kinds of social media opens up new perspectives on the city. Powerful city makers and officials can no longer dismiss the plurality of voices that resonate on the web what people like and dislike about city design and policies. Over the course of the year, the studio met with a broad variety of government officials, critical activists and commercial parties, both from Russia and abroad, to gather their views on the pros and cons of the current data revolution. In general, there are two main approaches that are being taken towards the significance and implications of the phenomenon of data and its increasing


на фестиваль Трансмедиале, и в Силиконовую долину, в СанФранциско. Это позволило студентам сформировать собственное мнение, чтобы потом обосновать его в своих проектах. Используя исследовательский подход Бруно Латура, студия попыталась оценить, какие существуют данные и как они описывают изменения, происходящие в Москве. В процессе работы рассматривались три вида информации: официальные данные, данные, производимые пользователями, и так называемые «альтернативные» данные (те, что не попадают под вышеперечисленные определения). Вскоре стало понятно, что разобраться совсем не просто: официальные данные часто неполные, противоречивые и путанные, а данные пользователей разрозненные, выборочные и мало о чем говорят. Возможно, в ближайшем будущем появятся новые инструменты, с помощью которых с неоднородным миром данных получится эффективно работать. В процессе работы над проектами студенты пытались изучить весь процесс работы с данными — от сбора и анализа до непосредственного применения. Некоторым даже удалось изобрести собственные инструменты. Среди тем студенческих проектов — концепция «умного города» как новая утопия; метро как источник данных; данные, производимые детьми; влияние данных на современное восприятие города; городской индекс, а также исследование о роли приборов в создании данных. Работа студии — одно из первых исследований, оценивающих масштаб и последствия грядущей цифровой революции.


digitalization. The first is critical, while the other, highly optimistic. To explore these extremes, the studio undertook two field trips – the first to Berlin, for the Transmediale festival, and subsequently to San Francisco and Silicon Valley. This allowed the students to understand better their own positions within the debates, and to reflect this in their proposals. Using Bruno Latour’s research approach, the studio started with collecting and exploring the availability of data from an open, innocent perspective to find traces of changing behaviors in Moscow. In doing so the focus was on three, complementary layers of data: official data, user-generated data, and other, new data sources. It soon became clear that it is far from easy to navigate in both the old and new worlds of data. While official data sources are often incomplete, confusing and contradicting each other, data generated through social media is scattered, selective and not representative for the population of Moscow. We foresee the introduction of a range of new data sources and tools in the years to come, that will adequately deal with the current fragmented world of data. The student projects covered the whole data chain, from collecting data to analyzing and using it. They used data from official sources as well as social media sites, and, in some cases, developed their own tools to gather data that is not yet available from any existing data source. Topics include smart city concept, the metro as a source of data, children-generated data, collecting data to trace cultural change or the identity of districts, the role of new data sources in perceiving Moscow, and the collection of sound data. In our view, the work of the studio stands at the brink of a data revolution with much more to be expected.


This book is designed for personal, non-commercial use. You must not use it in any other way, and, except as permitted under applicable law, you must not copy, translate, publish, licence or sell the book without our consent.


CONTENTS Introduction Key Map Moscow in Figures and Graphs

10 12

Studio research reports Frames of Mind Datalab Metro (Re)charge Tools Children-Generated Data Identity of Moscow Districts This is Smart-a!

14 24 40 56 64 74

Fieldtrips Berlin / San Francisco / London

91

Interviews Felicity Scott Christian Nold Matthew Dryhurst Kazys Varnelis

92 94 95 96

9


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6

Timothy Misir

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si

e -g ram t er ag ee us nst adsh i re sp itter tw square four Frames of Mind

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56

Identity of Moscow Districts

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The amount of data gathered and accumulated in the cities today gives everyone the opportunity to explore it from different sides and on different scales. The most intricate thing is to ask the right question.

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48

ChildrenGenerated Data

ta da al t en nm cs t ro sti hee ire i v ti ds na esntareation spuesvey q ur o s hot r p witte t


THEORY

DATA SPECIFIC

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66

This is Smart-a!

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SENSE

MANIPULATION

The data is biased starting from the point when it’s being gathered. The level of error in an organised database is twice as high as in raw data. Can we still rely on the impartiality of data?

Data itself says nothing to us. Numbers irrespective to each other are just symbols. This situation provides breeding ground for manipulation and techniques are well known. But how this process is happening nowadays in context of growing amount of data? 11


5547700 11503501

Moscow budget for 2013

6.1 mln

4945800

people visited museums

1 562 270 259 700

1028200

in 2012

rubles 1910

1960

2010

1994

Population

2002

2010

Female population

16.9

Total public transport ridership grew by

4.1%

3.7 mln 9.5

in 2012

citizens recieve different

11.0

1975

1990

2550%

subsidies

100%

2005

1998

200

100%

10 873

sim-cards

cafĂŠs can sell

100%

for every

2006

100

64%

alcohol

2001

2011

2002

Electricity consumption

2007

88 men

13186500 11306200

12681800

for every

100 women in Moscow

in Moscow

2012

2 tonnes

0.964

air contaminants emitted

0.848

every minute 2001

2006

2011

2003

Occupation (people)

1611

40 000

79% 68%

in 2012 2012

Municipal budget (billion rubles)

2001

2005

2009

250-400 liters of water

every day

Number of students

Moscow in figures & graphs Sources: Federal State Statistics Service (www.gks.ru), Moscow Government (mos.ru), Human Development Reports (hdr.undp.org), Department of Economic Policy and Development (depir.ru), Advanced Communications and Media (acm-consulting.com), Moscow Police (petrovka38.ru), Moscow metro (mosmetro.ru), Russian Education Statistics (stat.edu.ru),

12

2009

The average citizen consumes

100%

trees

252

2006

Human development index

planted 2008

citizens

Fresh water consumption

Τhere are

2004

2012

Construction works

Mortality rate

187%

2005


123%

213%

Ηighest rent debt

100%

Αverage salary

876702245.1 rubles 2001

2006

2011

50 000

100%

rubles

2003

Private cars

2006

2009

Pre-schoolers

5015300

Αverage speed of metro train

41.61 km/h

4120200

1994

Moscow’s Human Development Index

0.S964

2002

(the highest in Russia)

2010

73.6

64.4

1994

Male population

1975

1990

4123

pharmacies

7 .8

2008

Life expectancy at birth (years)

13.8

11.0

2001

2005

population

11 503 501

100%

2001

Birth rate

Moscow’s

195%

2006

2011

Housing built

173 628

Αverage metro trip

14.43 km

crimes

100%

2001

2006

100%

recorded in Moscow in 2011

74%

198%

2011

2001

Gas consumption

2006

2011

Waste water emission 10021556.8

76850000 64430000 60840000

2012

2014

2016

”Informational city” investments (rubles)

75.3

average life expectancy

8248652

1727

the number of schools in Moscow

1159034

2001

2006

2011

Gross regional product (mln. rubles)

A preliminary investigation of the city through numbers. All data was taken from openly available sources, which provide statistics in various fields from demographics to transport. Such an overview gives a general snapshot of 40 parameters of Moscow over different periods of time up to the present, thus showing an image of the city from a macro-statistical point of view.

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FR A MES OF M IN D I m a g e a b ilit y a n d le g ib ilit y in c o n t e m p o r a r y M o s c o w Timothy Misir

Where the physical environment is no longer the main source of cognitive cues, and tangible and physical spaces and places in the landscape are far less significant in contributing to our reading of the environment, how does one orientate and engage in space? This article explores how

the

networked

condition

contributes to creating an image of the city.

14


in tr o d u c tio n In 1960 Kevin Lynch published his seminal treatise on urban design, The Image of the City, focusing on the effects of physical form on spatial cognition, based on his analysis of Los Angeles, Boston and Jersey City. Widely regarded as a canonical text of urban design and planning, The Image of the City has been widely quoted again and again, and regarded as the paramount understanding of sense-making in cities, with its concepts still reflected in current urban design thinking. The aim of this project is to look at Moscow’s legibility and imageability in the age of Foursquare, where thinking and processing is replaced by code and machines, and user-generated content and locative media are contributing to making sense of the city. Even if the physical environment is no longer the main source of cognitive cues, as a result of one’s increased use of mobile mapping applications, and tangible and physical spaces and places in the landscape are far less significant in contributing to our cognitive reading of the environment, the city continues to be readable on other levels, especially beyond its functional meaning. Lynch’s methodology required conducting numerous interviews with city inhabitants, involving discussions of photographs of places, producing mental sketch maps, and also field reconnaissance to see how the city was presenting itself to them. The results would then be synthesized to produce a general public image of the city. This was a long and tedious process and explained his small sample size. He approached the city from the perspective of the user, specifically the pedestrian that makes use of visual cues to navigate the city at the ground level. He broke down the cities into their fixed forms, defining five types of urban elements: nodes, paths, edges, districts and landmarks. He hypothesized that together they influenced how city inhabitants read and made sense of their environment by aligning the different parts of a city into a coherent mental image. He believed that individuals formed personal interpretations and understandings of their environment based on their reading of its structure and physical form. The clarity of the landscape from its physical and spatial characteristics he termed ‘legibility’. The visual quality of the environment and its mental representation in observers, termed

‘imageability’, seems to imply a deeper emotional and personal connection with the environment, though he used it quite interchangeably with ‘legibility’. He stated that ‘if the city image is strong and clear, the viewer receives a certain degree of emotional security, allowing them to pursue their own aims in the city without anxiety’, as opposed to disorientation in an illegible city.1 Now we are able to find out where people go, how they move through the city, and what sort of words they associate with places through publically shared data found on social media networks, An attempt is made to use this data to see how an image of the city is being created in the networked age, and what additional ‘elements’ might be used to make sense of the contemporary city. Particularly, from user impressions, the vernacular geography of places and the ad-hoc networks and extended personal spaces contribute to a collective image of a place. The aim of this project is to look at Moscow’s legibility and imageability in the age of Foursquare, where thinking and processing is replaced by code and machines, and usergenerated content and locative media are contributing to making sense of the city. Even if the physical environment is no longer the main source of cognitive cues, and tangible and physical spaces and places in the landscape are far less significant in contributing to our cognitive reading of the environment, the city continues to be readable on other levels.

plac e s in c o d e d sp ac e M o sc o w Respondents from a small sample group of interviews conducted to gather opinions about orientation in Moscow all cited the city’s circular form and concentration of activity in the centre (Fig. 1). The most prominent feature in defining the city’s limits was the Moscow Ring Road (MKAD), which circulates the periphery of Moscow. The three inner ring roads that radiate around the city centre on different levels also provide reference for orientation alongside a few main boulevards and arterial roads, most of which begin somewhere around the Kremlin and link the city centre to the outlying districts. All these roads are strong paths, and, for the most part, boundaries in the Lynchian sense. The Red Square and seven prominent Stalinist skyscrapers that are dotted around the city centre loom large over the uniform landscape were the most com monly

15


Tv er

sk

ay a St re

et

Le

ni

ns

ky

Pr os

pe

kt

Arbat

landmark unknown areas point of confusion Fig. 1. Basic sketch map of Moscow made in the Lynch method

cited landmarks, orienting many respondents in the city centre (Fig. 2). The Moskva River, that meanders through the territory between the north-east and south-west was both mentioned as a prominent path and boundary. But at ground level, Moscow’s legibility is not particularly clear. For drivers, following one-way streets makes navigating the city difficult and breaks one’s continuous reading of the landscape. For pedestrians, the main roads are almost like edges, as they often divided parts of the city from another. The com mon problems cited that seem to prevent a coherent reading of the city include traversing the city’s large boulevards and big streets – along which prominent landmarks such as signs seem to be absent – lie almost identical buildings that do not increase the area’s legibility, lacking distinct facades and identifiable characteristics. Long building blocks and the lack of access between and around them mean that one often has to make large detours to reach the other side of a building or to cross the street. The large streets, like Tverskaya Street and any of the ring roads, are impossible to cross without an underpass, which are spaced far apart. Navigating through traffic intersections at street level become complex tasks. Some points of confusion mentioned include Leninskiy Prospekt, Lubyanka, Tulskaya, or Oktyabr’skaya (Fig. 3) and crossing the Moskva River (Fig. 4), all of which involve numerous long waits at traffic lights and several detours. Moving away

16

Moscow: Some elements of the city (user-uploaded images and impressions, from top) Fig 2. Landmark (Kotelnicheskaya embankment building) Fig 3. Node (junction at Oktyabr’skaya Fig 4. Edge/path (Moskva River)

from the city centre, the environment becomes even less identifiable, especially on reaching the microrayons, where most of the city’s inhabitants live, predominantly in standardized Soviet-built panel block apartment buildings, in neighbourhoods that lack distinctiveness from each other. As such, city districts were hard to define, and were usually just a distinction between the city centre and the periphery. However, different parts of the city have different associations and meanings for citizens, that contribute to its overall image. Furthermore, these experiences are now extended and enhanced by mobile technologies and locative media, and


are shared online. However, The Image of the City was written in the preinternet age and only considered physical form. In the networked age, data and the physical context are closely intertwined; information is ambient and almost every person and place in the city is networked and the contemporary experience of the city is built and structured around information networks. As individuals are able to interact with space in new ways, do the concepts of legibility and imageability continue to be relevant in the contemporary city, and what are the new concepts that help us organize the city cognitively? The effect of networks on the contemporary city cannot be understated. Defining a network as an organizational paradigm, Manuel Castells states that it is simply, ‘a set of interconnected nodes.. selfreconfigurable, complex structures of com munication that ensure at the same time unity of the purpose and the flexibility of its execution, by the capacity to adapt to the operating environment’.2 While networks are not a new phenomenon they have become the dominant organizational form and structural logic, influencing social, political and economic life as a result of the new technological environment. The city is a space of places, but the networked city is also a space of flows, the latter of which is a pattern of interaction that Castells described as an abstract notion of where space and time interact with society in the digital age. Networks connect people and places, and the space of flows becomes an expression of power and dominance, and especially so in the late-capitalist, post-Fordist period defined by capitalist-driven development, which it is organised around.3 Location-based media is affecting how one engages with and experiences urban space. Individuals now have all the information about places they would ever need and are able to choose and filter them to suit particular interests. One tunes out of the im mediate environment and pays less attention to surroundings where turn-byturn directions are provided by in-car GPS-powered navigation systems or on one’s mobile phone. Places become like nodes suspended within networks, meaning that, at a certain level, topography and landmarks lose their importance. The landscape is ‘flattened’ and, without the landmarks and other visual cues one normally uses as a way of finding, reduced to a vast terrain of roads and highways, with navigational indicators alerting us to turn at the next junction. Instead, we now receive information about our particular location

and environs without explicitly calling out for it. One finds out about and travels to new places – shops, cafes, bars, etc. not by word of mouth or advertisements but through systems that tailor recom mendations to places of interest based on the user’s specified location and history, and from pictures and com ments about places that pop up on our news feed. This means that, anywhere that is not a node (or placed or represented within a network) gradually loses significance.

m e t h o d olo g y Publicly shared Twitter activity in Moscow was gathered over two 24-hour periods, on a weekday and the same on a weekend. Being time-stamped and geo-located, one can use this database to see behavioural and cultural patterns of inhabitants of the city, and their spatial and geotemporal patterns. This data set included approximately 37000 and 35000 tweets for the weekday and weekend periods respectively. From this stream Foursquare check-ins, tips and tags were gathered, as well as locations and hashtags of Instagram uploads, and the location and content of tweets. There are clearly limitations to making conclusions based on data gathered from social media, not to mention the limited demographic ground it covers, but these case studies (Foursquare, Instagram,

weekend weekday residential area Fig 5. Foursquare

check-ins in Moscow during sample period (24 hrs)

17


and Facebook) are not about their precise content but rather looking at their nature and how they relate to the city that is represented digitally. The three casestudies show that how location-based media is both affects and shows how one engages with and experiences urban space. They serve as a sufficient proxy for revealing place and activity networks in Moscow, and illustrate how digital networks contribute to one’s reading of the city, especially since this particular demographic is contributing the most to how places are being represented in digital space. Looking at the distribution of Foursquare check-ins, most activity is concentrated in the city centre and main transport conduits, though there are also many areas with little or no activity. Weekday and weekend patterns also differed considerably (Fig. 5). The production of data in space is not uniform, and far more concentrated in some locations than others. At times it is even at odds with the physical architecture and space of the city. Because of their digital representation, all these points also function as landmarks, though in a different sense. In the networked age, people also orient themselves in relation to peers on a network, and their points of interest and locations. Their distribution is uneven meaning certain parts of the city are being ‘imaged’ far more than others and play a disproportionate role in contributing to one’s image of Moscow. Where for Lynch edges were linear breaks in continuity, the digitally under-represented places in the city and places that are almost never mentioned are the present day ‘edges’: where the network ends (Fig. 13).

Fig. 6 #rainbow #moscow #sunset #rain #summer

Fig. 7 #summer # # # #

come tagged with metadata such as georeferenced coordinates and hashtags (Fig. 6, 7). Visual form plays a significant role in the experience of places, and this was seen through the words users ascribed to images taken in Moscow, though an analysis of hashtag frequency only revealed the obvious, and it was more interesting to qualitatively analyze photographs and users individually, and not analyze collectively, as this yielded more interesting findings and revealed the personalized geographies of the city. The analysis of linguistic content that accompany tweets, checkins and images will provide a deeper understanding of how individuals give meaning to their lived environment and insight into popular topics discussed in the city, specifically because they are tied to particular locations. With a larger dataset, one would be able to find out area-specific topics of interest and more precise time-related discussion topics –

The situation is best described by McCullough, ‘The digital layer accumulates better in some places than in others.. To put it another way, not all is flow in the space of flows.. the flows of people, goods, and information require fixed channels, switches, and fittings to become most effective’.4 As a result, some places have becomes more successful than others, with individuals encountering them more than others, whether in real life or digitally via images circulated, or through com ments, tips and check-ins shared on networks, contributing in forming one’s image of the city, despite them not being elements in Lynch’s sense. The photographs posted on Instagram, a photo sharing and social network, collectively describe the rhythm of the city and its patterns of life. As a repository of user-contributed images, it provides information on how individuals are seeing and describing Moscow as they

18

Fig. 8. Communities and relationships in the Moscow River Runners network Nodes (members) sized according to connections and clustered based on interactivity


for example, when people begin planning meals and look for recom mendations, or what kinds of discussions are being generated from particular locales or categories of places, to what sorts of tags are more closely associated with particular areas of the city. Looking at private geographies that are being shared online, one can conclude that a micro-geography of personalized routes and narratives are replacing collectively shared public landmarks. People are the products of multiple networks, and fluid geographies are being created and processes of connection and disconnection are happening concurrently among individuals based on interests. Connections between nodes make a network. Without these connections the nodes cease to be significant, thus we become the product of where we situate ourselves. Looking at social networks shows how individuals in digital space function in the same manner as physical nodes: where paths converge and a concentration of activity is found. To understand the city in the networked age, one must understand the relationship of its places within their networks, as they receive their meaning from them, and their function relates from their ‘nodal role in the specific networks to which they belong’, as Castells explains, ‘Because practices are networked, so is their space’.5 Certain tribes play a more significant role in creating an image of the city, especially through networks and com munities, where one person’s image or reading of the city becomes etched into the collective memory of individuals in the same network. Data was extracted from the Moscow River Runners Facebook group, a social running club, with 910 members (nodes) and within this, 5316 relationships (edges), to visualize how networks contribute to building an image of a place and create new geographies and orientations in space (Fig. 8). Com ments, likes and tips that circulate in Twitter and Foursquare also function in the same manner, building an online history of places, influencing individual perceptions, such as whether it is a good or bad place and attributing other values to places, In this network, photographs and com ments posted by users to the group that illustrates how space is being used (for example, of a new running route, a location with a nice view, or an interesting observation during a run) then become points of reference for other members of the group (Fig. 9, 10). While Lynch’s ‘districts’ were areas with recognizable, com mon identifying characters, this concept can be extended

Fig. 9 #cold #snow #moscow

Fig. 10 #park #vdnkh

to our reading of com munities in the digital age, and how they relate to space, as com munities link places to each other, for example, based on shared interests. So, in digital space, districts do not necessarily have to be geographically contiguous.

disc u s sio n As more of the physical world is becoming digitally catalogued, one’s experience of space, and even getting there is mediated by technological infrastructures so individuals conceptualize space differently. One might even add that digital generations perceive space differently anyway, as they have never done otherwise. Ironically, the top five places in Moscow, which total about 1 million check-ins, are actually non-places in the Augéian sense - three are malls that are more or less identical to each other, containing the same chain stores and cafés, while the other two are airports. Of the top 20 locations, ten are malls, while five are either train terminals or airports (source: 4sqstat.ru). To Marc Augé, a non-place is insignificant because they are not symbolized and function as places of transience.6 However, they are among the most popular places in Moscow, and individuals’ attachment to them can be seen through the amount of photos tagged and uploaded, including personal photos, not just those of the sites themselves. Looking at the list of venue check-in popularity, The occupation of physical space seems to require, most importantly, the availability of mobile, wireless or 3G signals (the Foursquare list ‘Free WiFi spots in Moscow’ has 1773 followers, and includes most of the venues with the highest number of check-ins), as well as seating or loitering space (for example, in open spaces or cafés), the availability of various forms of fuel and stimuli (such as food, nicotine, caffeine or alcohol), and shelter, warmth, and light. Thus, one can assume that in Moscow, people orientate

19


Fig. 11. Leingradskiy Railway Terminal 8th most popular location in Moscow 472 tips, on 120 lists, 6015 photos. Place rating: 8.4/10 (user-contributed picture, foursquare.com)

Fig. 12. Evropeisky Mall 2nd most popular place in Moscow 626 tips, on 267 lists, 5983 photos. Place rating 9/10. (user-contributed picture, foursquare.com)

themselves around railway stations/airports (Fig. 11), malls (Fig. 12), and com mercial food chains like Starbucks (which has 11 locations in Moscow’s top 250 places on Foursquare). The only outdoor place that is well represented is Gorky Park, at 6th position, which, coincidentally, provides free open WiFi access. The only other outdoor spaces that rank highly are Red Square, New Arbat St. and Arbat St. (20th, 21st, 25th position respectively).

homogenous, borderless urban landscape based on consumption, whose form allowed for it to expand infinitely. There, the street and urban form mattered little in an environment that was subordinate to electronic media that had accelerated trade and com merce to an absurd degree, and, in turn, caused the metropolis to unravel.7 Certainly, the digitization of cities and the growth of associated infrastructure are closely linked to capitalism, enabling the seamless and instantaneous movement of capital and culture, and for increased consumption. In writing about the relationship between architecture in the period of late capitalism and its relationship to the city, Kazys Varnelis highlighted the ‘obsolescence of architectural form today’, arguing that the ‘dominance of the visual’ in recent architectural history was an aberration, anticipating an im material age, a time where visual elements play a much lesser role in the pursuit for organizational efficiency and profitability.8 Perhaps, then, in this im material age, a city’s lack of physical imageability is being compensated by the increase in the digital presence of places.

With the pre-eminence of networks over built structures, it seems that Lynch’s concepts are ill-suited to orientate individuals, where the virtual representation of space comes to define its physical form. However, orientation and engagement are still necessary in the networked age, where anxiety reduction seems more important than before, especially with physical places providing even less legibility than before. A melding of physical and virtual domains is allowing for a more malleable identity and for the city to be shaped and reconfigured by its users. Because of this, a far more subjective experience of space, reflecting multiple personal geographies based on one’s interests and demands, is enabled. People consume, produce and broadcast on their own networks, but, even if everyone is living in personal geographies, the digital is being used to highlight the physical. Com merce and infrastructural networks have long influenced the physical form of cities. In the late 1960s, Archizoom conceptualized a city without qualities, where its infrastructure, not built structure, was not the main organizing feature. Titled No-Stop City, it described an exaggerated model of the capitalist city of the future; a model of a uniform,

20

At the same time, we observe parallel processes enhancing the city’s digital and virtual layers, opening up its borders and edges. Places and their uses are not fixed, as people are defining their own use of space, so the contemporary city changes residually, based on demand. The city functions more like an interface for individuals engaging in the virtual network. Physical architecture and urban design becomes less important in this sense, so city governments and authorities cannot shape the city as they like it and ‘create’ success anymore, as users give implicit feedback through check-ins,


recom mendations and tips broadcast on online networks. The digital layer does not merely overlay the city, but augments it and is a constituent part of the processes that create it, as Dodge & Kitchin explain, ‘In Code/Space, code dominates the production of space, explicitly mediating social-spatial processes and experience’.9 ‘Ubiquitous’, ‘embedded’, ‘ephemeral’, ‘ambient’, ‘situated’, ‘distributed’, and ‘networked’ are some terms that have been used to describe the omnipresent digital space of the city, regulating its rhythms of life. Cities are still spaces to be experienced sensually, though physical elements having less salience in digitised space. The legibility of the spatial structure of the city in Lynch’s sense is thus important only to a certain extent, as the digital layer allows for other ways of contributing toward legibility and imageability. While spatial cognition relies on environmental meanings they are also constructed virtually and online by others. If places are significant because of their shared functions and meanings, and if groups or com munities contribute to one’s understanding of place, then it is far more important for individuals to be embedded in networks.

c o n clu sio n The concepts of legibility and imageability have long been used to explain orientation and engagement with the environment – they are not dead in contemporary Moscow, though how they are formed might have changed. This article has attempted to use social media data to explore how it can contribtue to a creating an image of the city for its inhabitants. To understand the city in the networked age, one must understand the relationship of its places within their networks, as they receive their meaning from them, and their function relating to their ‘nodal role in the specific networks to which they belong’, as Castells explains, ‘Because practices are networked, so is their space’.9 The elements of the city are mutating into the virtual world, with completely new concepts emerging. Perhaps, then, new elements of the city that take into account the contemporary condition need to be defined to complement Kevin Lynch’s five. These might include: Media (the new public space around which culture is organised), Infrastructure (physical and virtual, around which the space of flows is organised), Consumption (retail and commerce, which guides patterns of movement and navigation,

and determines media perception of places), and, lastly, Portals (points of access into the network, for example cafés and wireless zones, or various social networks and communities within them). While the city and the urban environment are constantly evolving, its landmarks and fixed forms still exist, though they might not serve the purpose they once did in providing sight lines and orientation. Space is not disappearing but, with more of a virtual presence, imageability seems to be constructed differently in the networked age with other elements. Spaces are being replicated with a variety of meanings and uses, reflecting networked and temporal realities. There are different ways of experiencing one’s surroundings, and this often happens socially and through networks. Lynch spoke about a user’s comfort level felt when the city was more legible, knowing where they were in space and in relation to visible landmarks. Now, this anchoring is achieved by placing one’s self in networks. Though one might argue that it constrains choices, technology is creating new meanings of environment and self. One’s image of the city continues to be a product of a two-way relationship between the individual and his/her environment, but the technological and social shift allows for new ways of experiencing the city, and as a result, individuals are able to shape their own environment. Moscow needs to adapt to support the digital and mobile being, to whom official program ming or zoning of space matters little. Space and architecture shaping it should thus not be limiting, and improving public infrastructure must be made to make the city compatible to its occupation and appropriation by users. For example, by increasing the number of public toilets, public lockers, co-working spaces, WiFi hotspots, bicycle repair points, mobile and portable device charging stations, etc. This will encourage users to define and inhabit places to a higher degree, resulting a in physical environment that is not so disconnected from the virtual world, contributing to a more coherent reading of the urban environment for the user.

21


r e fer e n c e s Lynch, Kevin (1960) The Image of the City (Cambridge: MIT Press). Castells,

Manuel

(2004).

‘Informationalism,

Networks,

and

the Network Society: A Theoretical Blueprint’, The Network Society: A Cross-Cultural Perspective (Castells, M., ed.) (Northamption, MA: Edward Elgar). Castells, Manuel (2000). The Rise of the Network Society: The Information Age: Economy, Society and Culture, Vol. 1 (Information Age), 2nd ed. (Oxford: Blackwell). McCullough, Malcolm (2007). ‘New Media Urbanism’, Environment and Planning B: Planning and Design 2007, V.34. Castells,

Manuel.

(2004).

‘Informationalism,

Networks,

and the Network Society: A Theoretical Blueprint’, The Network Society: A Cross-Cultural Perspective (Castells, M., ed.) (Northam ption, MA: Edward Elgar). Augé, Marc. (1995) Non-Places: Introduction to an Anthropology of Supermodernity. 1st Edition. (London: Verso). Archizoom

Associates

(1971).

‘No-Stop

City.

Residential

Parkings. Climatic Universal Sistem’, Domus 496, March 1971, 53. Varnelis, Kazys (2003). ‘A Brief History of Horizontality’, Pasajes de Arquitectura y Critica, March 2003. Web: http:// varnelis.net/articles/horizontality. Kitchin, Rob & Martin Dodge (2011) Code/Space: Software and Everyday Life (Cambridge: MIT Press).

For places to be strongly embedded in the network and occupied by people, and, as a result, be highly visible in the digital world, there needs to be free wifi, enough places to loiter, and an ample selection of food options. (User photo: Atrium Mall, Kurskaya - 8th most popular venue in Moscow)

Fig. 13 (below)

E d g e s i n d ig it al s p a c e

Limited wireless connectivity

weekend market not reflected (no one promoting and sharing event)

Limited wireless connectivity

shop not listed on foursquare system (no one can check in at place)

22


D ATA L A B METRO Urban data g o e s p e r s o n al Gulnaz Aksenova & Artur Shakhbazyan

“Great

leaps

knowledge

have

in

scientific

almost

always

been preceded by improvements in methods of measurement or analysis� - Mike Snyder

24


i n t r o d u c t i o n There is an emerging comprehension of a city as a self-organised adaptive system based on interactions of various proponents, informational feedback loops, pattern recognitions and indirect control (Priya and Cresswell, 2008). As Johnson says: ‘the city is a pattern in time’ (Johnson, 2013). City networks leave traces. Nowadays, our world is becoming more and more digitized. Therefore, along with physical ones, city networks also produce digital traces. Digital traces of any action made using connected device are somehow recorded and stored. The more actions done, the more traces left. Millions of people leave physical and online traces which later on can be collected, organized and analyzed. There is an assumption that these traces could help us to reveal some hidden patterns or to understand deeper human behaviour (Batty et al., 2012). As Deleuze mentioned, a city modifies its citizens no less than citizens modify the city (Batty, 2012). Such modifications and interactions occurring between city inhabitants and city elements are continuously evolving through time. How to understand and trace these interactions, however, still remains a challenge (Johnson, 2013). The emerging revolution of the ‘Big Data’ (Image 1) concept of tracking data generated by individuals, infrastructure and the nature promises to fundamentally change our cities in terms of bringing greater insights and knowledge for better decision-making (Cress and Merriman, 2011). Big Data is generated by a multitude of digital traces. It is collected with the use

5 V’s of Big Data

Image 1. 5V’s of Big Data

Value Velocity Veracity Volume Variety

of sensors registering climate, traffic, social media content, purchase transactions records, cell phone, GPS signals and so on. Big, in this case, is more than just a size; it is an opportunity to find insights in emerging types of data (Carter, Dec 2012). It may even help to understand the relationship between human behaviour and physical sciences (Carter, Dec 2012). But it should be clear that Big Data cannot be a replacement for the way things being done today, but could be an anticipated extension (Eaton et al., 2012). There is a vigorous discussion in the world about whether this data could actually have a real value, or bring even more noise into the concept of data overall. Nevertheless, Big Data has gained considerable support from such domains as business, marketing, medicine and urban planning. The main purpose of this research is an attempt, through the series of experiments, to investigate the potential of data for urban planning and decision-making, and to explore the use of data collected from different sources such as statistics, social media, and, ultimately, people themselves, in order to improve our understanding of the relationship between citizens and the city. Taking into consideration the fact that the amount and diversity of city elements is enormous, it was decided to focus on a particular aspect of a city and to explore the diverse nature of urban data with one particular case. The case of Moscow Metro was chosen for several reasons. First of all, metro is a representation of city infrastructure and its citizens at the same time. As marketeers claim, up to 80% of citizens, representing practically all social classes, use Metro on a regular basis ( Mosmetro, May 2013). Secondly, the area of urban transportation, which is undergoing substantial transformations nowadays, gives the space for experiments with new technologies and methods of working with data. In the course of research different types of urban data related to Metro were analyzed, a tool for data collection was developed and results of this analysis and data collection were interpreted in order to deduce possible potentials of data.

m e t h o d o l o g y As a matter of fact, data collection was an integral part of our research, which gave us the comprehension not just about the metro as a subject of research, but also about the methodology of working with data in general. Nowadays, when the processes

25


are happening much faster than ten years ago lack of up-to-date information could be an important issue. Historically, our ability to measure and monitor the city has been limited. Today, however, we are entering the era of quantification, when it becomes possible to measure practically every aspect of the environment. City data can be conceptually divided into several types, or layers, representing a multidimensional model of urban data, developed in the process of research. There are three interrelated rapidly growing categories of new data: crowd sourced, private, and ‘big’ data. (Goodspeed, 2011) There are certain cons and pros of each data type that exist in terms of data nature and time span. One of the oldest and most conservative, but nevertheless the most widely used, data type is statistics and macrodata. In the case of Moscow they have a number of issues. Generally, it presents only summarized information and sometimes different sources, even official ones, provide different numbers. Statistics and macrodata is a snapshot of the past, which in certain cases can be used as a basis for forecasting some general trends. Unfortunately, collected data often ends up within fragmented silos of bureaucracy as the responsible official agencies do not always represent the most efficient model. It is also obvious that such data shows only one sole point of view on an issue. Considerable limitation of other data types

Tagansko-Krasnopresnenskaya Serpuhovsko-Timiryazevskaya Zamoskvoreckaya Kalugsko-Rigskaya

Kahovskaya Butovskaya Arbatsko-Pokrovskaya Sokolnicheskaya

were also acknowledged, though, it is anticipated that a combination of multiple layers of various data types in conjunction with different time spans could give us a better perspective on the context. We distinguished four data layers for analysis of metro which included various datasets derived from different sources, but with a focus on what can tell us more about passengers and their experience, rather than about its technical characteristics. We started our analysis with openly available statistics. The second layer was user-generated data from location-based mobile social media. The third layer was Bio and Environmental data, which is an alternative data set, extracted using an electronic device specially developed for this research. The quality of data was evaluated according to five data qualities: veracity, velocity, volume, variety, value and time. Macrodata is a summarized data set and usually represents average numbers/statistics (Diez-Roux and Ana, 2002) (Image 2,4). Publicly available data was collected from the official site of Moscow Metro, as well as from the RosStat sources. There are five sources of publicly available data about the metro users: turnstile data, ticket sales data, emergency calls from intercom, incident statistics and temperature on stations. Collected data was scattered and fragmented and required extra formatting to satisfy the needs of research.

Lublinskaya Kalininskaya Kolcevaya

150000 120000 90000 60000 30000

6:00 7:00 8:00 7:00 8:00 9:00

MEN 55.1% ABOVE 46 38.5% MARRIED 53.8% HIGHER EDUCATION 72.2% WORKER, BUILDER 14.4%

WOMAN 53.3% ABOVE 46 26,7% MARRIED 48% HIGHER EDUCATION 72.2% SERVICE 22,7%

Image 2.

26

11:00 12:00

WOMAN 54.3% 19-22 YEARS OLD 24,7% NOT MARRIED 63% HIGHER EDUCATION 72.2% STUDENTS UNKNOWN %

23:00 00:00 00:00 01:00

WOMAN 54.4% 19-22 YEARS OLD 30.4% NOT MARRIED 51.9% HIGHER EDUCATION 72.2% STUDENTS 30.8%

WOMAN 60.8% 23-27 YEARS OLD 34.2% NOT MARRIED 57% HIGHER EDUCATION 62% STUDENTS 24.7%

MAN 69.7% 19-22 YEARS OLD 37.2% NOT MARRIED 64.9% HIGHER EDUCATION 76.9% SHOPPING MALL WORKERS24.7%

Image of metro passengers according to the time they use metro. Generalisation of metro user


User-Generated Data (UGD) is created and distributed (not necessarily directly) voluntarily by an individual or a group of people. It became especially widespread with the pervasion of digital communication and Internet. Nowadays any single person has the possibility to contribute to the global collection of data with his own device, opinion, story or just presence. The minimum requirements here are a source of electricity and computer or mobile device with network access (Keene). UGD is a part of big data concept. Rapid development of mobile communication technology is one of the main driving factors of the growing amount of UGD. Global penetration of mobile communication has reached 89 percent worldwide with 6.4 billion subscriptions (Johnson, 2013), in Moscow these figures are much higher: 37.2 million sim-cards in use and 199.9% of penetration (AC&M, 2013). Popularity and the mass availability of location-based social services, such as Panoramio or foursquare, also have an important role in the process of bringing the spatial dimension to UGD, which makes possible its space-related application, in our case in spatial planning and urban development. The main sources of UGD are mobile social networks. Metro passengers use location-based mobile services while they travel. They check in at metro stations, update their statuses and chat with friends, thus contributing to global databases of user-generated content.

Twitter and fousquare, as two examples of the most popular social services, were chosen for analysis. Twitter is a micro blogging service, allowing its users to share short statuses about what is going on with, and around, them. Initial study of mentions of Moscow Metro in Twitter revealed that the number of tweets which can be identified as related to Moscow Metro (geotagged and mentioning ‘metro’) is around 5 tweets per hour. Moreover, 4 out of 5 were simply a share of user’s foursquare check-in to their twitter account. It demonstrated that use of twitter in the metro is fairly low, and does not provide any relevant information. It also worth mentioning that Twitter has a considerable limitation of API which allows it to obtain only 10% of tweets by search criteria, and only over the last several days. All other information is closed and only available on a paid basis. Foursquare is a geo-based social network allowing a user to check-in at a place, stating that he is there at some particular moment of time. It also allows rating and “liking” places and leaving tips, describing their particular experience at this place. An API of foursquare gives more freedom and

GALVANIC SKIN RESPONSE SENSOR BODY TEMPERATURE SENSOR MICROPHONE - NOISE SENSOR LIGHT INTENSITY SENSOR HUMIDITY AND TEMPERATURE (AIR) SENSOR USB POWER PACK ELECTRONIC PROTOTYPING PLATFORM TEENSY++ LIQUID-CRYSTAL DISPLAY BUTTON 1 - BACKLIGHT SWITCH ON/OFF BUTTON 2 - RECORD TYPE SWITCH STATION/TUNNEL BUTTON 3 - RECORDING START/STOP Image 3. Device to measure Biodata and Environmental data

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MACRODATA

hani Pallasmaa (Pallasmaa, 2009). As sensory reality gradually developed towards unrivalled dominance of the sense of vision, we have to revise our experience in the metro. In such a place as the metro, where distances between people’s personal space is becoming smaller or may be invaded by others, haptic/bodily experience is becoming dominant (Bruno, 2002, Montagu, 1986, Pallasmaa, 2005, Wood, 2010). However, all senses, including vision, are extensions of the sense of touch; all sensory experiences are related to tactility (Pallasmaa, 2005). Every significant experience of a context or an environment is multi-sensory; qualities of matter, space and scale are measured by the eye, ear, nose, skin, tongue, skeleton and muscle (Montagu, 1986, Pallasmaa, 2005, Holl et al., 2007, Pallasmaa, 2009). Use of sight, sound, smell, taste, and touch all provide data about our environment.

TURNSTILE DATA (2008-2010)

? PASSENGER RIDERSHIP ACCORDING TO METRO LINES BUTOVSKAY

LUBLINSKO-DMITROVSKAY

SERPUHOVSKO--TIMIRYAZEVSKAY

SOKOLNICHESKAY

ARBATSKO-POKROVSKAY

KOLCEVAY

KALUGSKO-RIGSKAY

ZAMOSKVORECKAY-KAHOVSKAY

FILEVSKAY

KALININSKAY

TAGANSKO-KRASNOPRESNENSKAY

400 300 200 100

2008

2009

2011

2010

MONTHLY DISTRIBUTION OF RIDERSHIP IN ONE YEAR 2011

2008

8000

2009

6000

December

November

October

4000 September

August

July

June

May

April

March

February

January

2010

WEEKLY DISTRIBUTION OF RIDERSHIP IN ONE WEEK 2009

2010

20% 15%

2008

2011

10% 5% 0

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

Image 4

access to data in comparison to Twitter. Even though the detailed information about check-ins is closed, venues data is publicly available. Special scraping script was written which collected all possible information about each of 184 stations of Moscow metro presented in foursquare, namely: number of users, checked in at a station, overall number of check-ins for every station, how many likes each station has, how many tips are left for each station and what these tips are. In total, in 184 stations of Moscow Metro, 350 000 users checked-in 1 350 000 times. Such a volume of data was found sufficient for the purpose of the present research. In a metro we critically have to diagnose a psychological pathology of seeing, says Ju-

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‘Bio data’ is a term that is used in this research to describe data of biological processes in a human body and environmental parameters, and does not represent an original meaning as it is stated in a dictionary. It is an alternative source of data and is not available anywhere. Therefore, a wearable tool (Krylov, 2013) for data collection was designed particularly to measure alternative types of data (Image 3). The tool collects 6 types of data, including 2 sensors for biological processes data and 4 sensors for environmental data in real-time, and is able to work for 24 hours. It is anticipated that the control over the development of the tool and measurement of data might give the quality of data that is expected. The device is built using the open-source electronics platform created by Teensy++, which provides opensource software to network and control the devices as well as building the software. It is a representation of a concept ‘doit-yourself’ (DIY) that takes a lightweight approach without the help of experts in exploiting urban data. There is a sensor that can measure emotional state which is called Galvanic Skin Response sensor (GSR-sensor); used by Christian Nold in his Emotional Cartography (Nold, 2004), where he has visualized emotional experience using technology that measures stress levels in conjunction with geo-location. GSR is a biodata that represents electrical conductivity of one’s skin which fluctuates based on certain bodily conditions. We used this sensor to measure emotional states of metro users in order to understand how people feel at different stations and what contextual factors affect their emotional level and experience. These measurements were used to plot


MIDDAY TRIP 24/05/2013 500

NIGHT TRIP 22/05/2013

12:05 PM

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Image 5. Data collected during regular trips at day and night

0

NOISE LEVEL

Outside

Tunnel

Station

a map that highlights the point of high and low arousal. By sharing this data it is possible to construct maps that visualise where in a metro we, as a community, feel stress and excitement (Nold, 2004). The sensor was supplemented by another biodata sensor measuring body temperature and sensors that monitored air temperature, humidity, noise level and luminosity. Measurement of biodata can be conceived through multiple sequences of human situations and encounters in transitive spaces. It is anticipated that biodata collected as big data could be a valuable asset for objective characteristics of the city as a self-organised organism whose biological processes are measured, recorded and visualised in real time (Watts, 2013). Psychologist Robert Levine states that every city runs on a particular beat at a given time, the same as Metro (Levine, 2006). According to physicist Jeffrey West, the count of beats per unit time can be an indicator of the objective characteristics of the city (Greenwood, 2012). Measurement of multiple sequences of a metro user at particular times of the day in conjunction with recording data every half of the second might give an objective characteristic to the measurement of embodied experience.

NOISE LEVEL

350 300 250 200 envSound 150 100 50 0

Outside

Station

Outside

Tunnel

Outside

Station Station

Therefore, our measurements of one female 28-year-old of her regular late morning and night trips to Strelka Institute were complemented with visual documentation and voice expressions of her experiences. The trips were measured from home to Strelka Institute, thus monitoring not just data from in the metro, but also from outside. A measurement of the metro line (Sokolnicheskaya metro line) was conducted during midday and was not considered as a regular trip. She has visited 19 stations spending few minutes at each station. Results will be presented in the data analysis part.

f i n d i n g s & c o n c l u s i o n s Most of the collected statistics, except mapped hourly distribution, showed obvious results within expectations. Data, such as demographics, showed a limited ability to explore race, culture and social class. Considerable limitations in data about passenger traffic derive from the way it is

29


collected. Since Metro can only register entering passengers, it does not provide a complete picture of passenger traffic in the metro (Image 4). For instance, once visualized, it suggests that during morning rush hour stations within the central line are practically empty, which is, obviously, not representative of the reality. While the overall ridership can be estimated, more interesting characteristics, such as traffic on particular stations or even load of particular train coaches, are unachievable with the use of existing methods. It is anticipated that such data can be extracted from CCTV cameras located at the stations and in the trains, however, this data is not openly accessible and therefore cannot be considered for the time being, which is a shame. Temperature readings from stations are the only ‘alternative’ type of data (environmental) that is provided officially by Moscow Metro. First of all, readings are published once a month with no explanation of the particular time of the day they are taken. Taking into consideration the original purpose of this data, to monitor the compliance with health standards, especially in summer, when air temperature at some stations rise and can affect someone’s well-being, it seems senseless to publish it retrospectively. The only way this data can be valuable is to stream it in real-time, so passengers could be aware of possible inconveniences they would experience. The notion of real-time data brings us to the next data layer, which is social media content. Keeping in mind the incompleteness of user-generated data, it was compared to official statistics in order to appraise its validity, variations and biases. This type of data has higher levels of detail on topics previously difficult to study, such as movement patterns. It requires a certain level of skills, but at the same time provides access to this data. Data, scraped from foursquare, allowed the rating of metro stations by popularity and the comparison of this “rating” with official numbers on ridership. Resulting trend lines were strong enough to prove foursquare to be an appropriate data source for our research. Check-ins themselves are generally neutral, only demonstrating that a user has been in a particular “venue”. In this respect they are similar to quantitative statistics, allowing estimating number of visitors and, therefore, popularity of a place. By comparing number of unique users and overall number of check-ins for each station we estimate if users check-in more regularly

30

TOP-5 METRO STATIONS by number of check-ins Image 6

1. 2. 3. 4. 5.

Yugo-Zapadnaya 21 689 Kitay-gorod 20 313 Vykhino 19 512 Kiyevskaya 18 257 VDNKh 17 766

at different stations (Image 6-7). When we visualized this rate spatially and overlapped it with map of Moscow, we saw that stations with higher regularity are situated in residential areas and sleeping districts, while check-ins at stations in historical and business centre of Moscow are less regular. Users tend to check-in more regularly in places which feel more private to them or which they have some sort of personal connection with. The highest regularity is in private homes, offices and residential buildings, while the lowest rate is in public venues, like airports and shopping malls (Philipp Katz, 2012). It allowed us to conclude that people tend to “appropriate” stations around which they live or which they regularly use as their daily trip starting (or ending) point. At the same time stations in the centre of Moscow have a more “public” nature. A similar idea is described in Raz Schwartz’s article where he mentioned a special place attachment appearing for people that use social media at their favourite places. He gives


REGULARITY OF CHECK-INS Image 7

“death”, “survival”, “stink” were repeated many times by different people. They leave tips such as “Morning at Vykhino - is a fight for a place in the metro ( )”, “It smells like death here ( )”, “It is REALLY SCARY here ( !) ”, “HELL’s gate ( !)”, “People, I am in the ass of the world))) ( !!)))”, “It is a morning hell ( !!)”, “Hateeeee....aaaaaaa!!!! Disgusting and dirty place!!! ( !!!)”. And even though Vykhino is a fairly unattractive station in terms of architectural appearance, no tips mention that it is “ugly” or even “not beautiful”. Likewise, each station of Moscow Metro has a particular picture of what people like and dislike, represented through their online sharing. There is a strong connection between physical and virtual space and there is a strong correlation between people’s behaviour online and in real life according to Tim Cress and Peter Merriman. People’s ties to physical spaces are mediated by location-based technology such as foursquare (Cress and Merriman, 2011).

less

more residential zones an example of a person who uses foursquare in a particular Starbucks coffee shop, and each time he goes to another Starbucks he makes a post: “I feel like I’m betraying my @Foursquare mayorship by going to the other Starbucks” (Schwartz, 2012). In Foursquare there are also options, such as “like/dislike” buttons and “tips”, which allow users to express their opinions and share their experience, and provide more qualitative data about the venues. According to this media content, passengers tend to react mainly on social experience, such as interaction with people around them, or on sensory experience, such as smell or discomfort, happening in the metro. Visual appearance of the station plays a minor role in everyday passenger experience, even though Moscow metro is considered to be among the most beautiful ones, with the most stations being architectural monuments. For example, people leaving tips in Foursquare at the most overloaded station Vykhino ( ) associate this station with hell and the words “hot”, “hell”, “scary”,

Certain documentation of passengers’ everyday life happens on foursquare. One might call it a diary of one’s relationship with the places which he has special ties with. The term ‘Place Attachment’ represents a symbolic relationship that is created by people who give culturally shared emotional meanings to a particular place (Schwartz, 2012). This in turn is argued to provide the basis for both the individual and a group understanding of their local surroundings. The same is happening at the metro stations: in such a highly transitive space, with thousands of people coming to the same stations every day, there is a collective/group understanding of a place as their favourite station. They make posts like ‘there is nothing better than my dear Yuzhka)) ( !))’ - this is a tip from one of the busiest stations in the whole Moscow Metro, Yugo-Zapadnaya. Routine makes us feel differently about places; our senses become used to familiar elements of the context and develop the attachment, which, in turn, is transmitted to social networks. Context, which influences our behaviour in the metro, is not limited to social experiences, but also includes unconscious factors, not always clearly expressed in a direct way. These factors can be identified with the use of bio-sensing technologies to measure not just individuals but populations as well.

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YUGOZAPADNAYA

PROSPEKT VERNADSKOGO

UNIVERSITET

VOROBYOVY GORY

SPORTIVNAYA

FRUNZENSKAYA

PARK KULTURY

KROPOTKINSKAYA

BIBLIOTEKA IMENI LENINA

OHOTNY RYAD

DATA TELLS A STORY: TRIP ACROSS 19 STATIONS OF SOKOLNICHESKAYA (RED) 17/05/2013 11:36 am Coming home, Strelka is my home ha-ha =)

STRESS LEVEL - GALVANIC SKIN RESPONSE (kOhm) 500

I have never been here

Policeman is looking at me :0

I am excited :)

400 300 200 100 0

No stress for wearing device

Personal attachments are connected to memory or special feelings

31

BODY TEMPERATURE (C)

t

31

31

32

31

30

29

32

31

31

27

NOISE LEVEL (dB) 2:30 min -60

0

30

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-40 -20 0

LUMINOCITY INTENSITY (%) 900 600 300 0

ENVIRONMENTAL HUMIDITY (%)

38 36 34 32 30

34

34

32

34

34

32

t

ENVIRONMENTAL TEMPERATURE (C)

28 26 24

25

24

5

4

24

23

24

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CROWD (%) 3

2

3

2

VISUAL SENSORY (CAMERA IMAGE): I SEE

32

25

3

5

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4

3

4

6

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6

46:30

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48


LUBYANKA

CHISTYE PRUDY

KRASNYE VOROTA

KOMSOMOLSKAYA

KRASNOSELSKAYA

SOKOLNIKI

PREOBRAZHENSKAY PLOSHAD

CHERKIZOVSKAYA

ULITSA PODBELSKOGO

) LINE OF MOSCOW METRO

I am hungry and tired

Old lady carying heavy bag upstairs makes me sad.... :(

Going home to eat!! Yess!!

500 400 300 200 100 0

No feelings to uknown stations

d

8:00

14:01 pm

someone smiling called me ‘Terrorist’ =O and took a picture of me for instagram

Emotions are from experiences

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28 26 24


The biodata experiment provided further evidence that the social factor is the one influencing passenger experience the most (Image 8). As our preliminary experiments demonstrated, levels of arousal significantly increased either as particular memories were evoked (at Kropotkinskaya station, which was strongly associated with a location of Strelka) or during the conversation with a stranger in the train. At stations where nothing was happening and few people were around arousal levels significantly went down. It was obvious that the visual appearance of stations did not affect user emotions. At the same time, additional experiments demonstrated that contextual changes while entering the metro from the street could affect the passenger’s emotions (Image 5), but, again, it is not absolutely clear if these changes were objective ones (noise, light etc.) and not related to subjective reactions. There is a room for further research. The subjective nature of biodata requires additional interpretation, which is the necessary element for making a true and meaningful record of one’s experience, which, actually, is not making the result any more objective. However, Leibniz stated that the gap between the physical and the subjective is unbridgeable (Cole, 1983). In return, we can state that the collection of data that represents shared experience is a conceptual challenge and question. As Christian Nold questioned (Nold, 2013):“Can we really blend together our emotions and experiences to construct a totally shared vision of place?” In pursuit of objectivity, an extra layer of data ‘survey’ was added which, on the one hand, was as basic as macrodata, but, on the other hand, allowed the so much needed generalization of particular experiences, expressed by individuals. Some results also provided extra evidence for some conclusions made out of previous analysis. In a similar way as in the foursquare case, respondents used their opportunity to express their complaints about minor and major negative factors in the metro. A direct question about personal attachment to some stations was answered positively by 60% of respondents.It also worth mentioning that 90% of respondents would appreciate having internet connection in trains and on stations, which demonstrates their interest in being connected while in metro, and should be considered as a potential for user-generated data to become more accurate and meaningful. To conclude, the experimental research

34

described above demonstrated the possibilities and methods of collecting different types of data about passengers of the Moscow Metro, a highly representative group of citizens who can, and do, provide large amounts of data related to their urban experience. The most important thing here is that all data is describing a significantly bigger context than isolated space of interconnected underground stations. Almost every bit of data can contribute to better understanding of aboveground areas around metro stations, and, combined, of the city in general. By way of example, value of data originating from metro users is described in the research, conducted by UCL and Yahoo researchers Chris Smith, Daniele Quercia and Licia Capra (Smith et al., 2013). Based on data collected with use of the automated fare collection system of London Rail they managed to “build a classification model that identifies areas of high deprivation” and “demonstrate a significant link between census area measurements of deprivation in multiple domains, and patterns of passenger flow in public transport systems”. Authors claim that predictions based on transit data could provide the basis for “city health monitor” and, if communicated to decision-makers in real-time, can significantly facilitate the process of identification of deprived urban areas and increase the efficiency of regeneration initiatives, including community-directed projects and campaigns.

p r o j e c t The city needs data. Personal meetings and interviews with city stakeholders demonstrated that, in order to come up with planning decisions, they need accurate and reliable information about all possible aspects of city life. Citizens are the main generators of city data, and more than half of them use the metro every day. The metro is the place where you can see a diverse range of people and their thoughts and habits. It is becoming more than just transport. It becomes a part of their everyday lives socially, and public space spatially takes on the same character as streets, museums, airports or shopping malls. Each station is unique in terms of architectural appearance; human scale is changing all the time. The regulated environment of the metro forces passengers to adapt to it and behave alike. They are bounded by a strict set of rules and obligatory procedures of passing through turnstiles, not running on an escalator, not wearing dirty clothes, not carrying oversized luggage or bicycles. They see the same things, hear the same sounds and follow more or less the same


Image 9.

routes. All this creates an intrinsic contextual equality which can be compared to a civic laboratory, where experiments are conducted in specific conditions. Travel behaviour in the metro is more than just a way of getting from A to B; it has a contextual meaning (Auge and Conley, 2002). Marc Augé in his work argues that “tourists have to climb the Eiffel Tower so as to see the city of Paris, but the Parisians do not”. This is because the Parisians are aware of what to do to see the city. For instance, Parisians know that they have to go to the metro to see the city of Paris, instead of climbing the Eiffel Tower. It is a fascinating fact that Muscovites are very much conversant with ambiguous spaces of the metro, as well as Parisians, and the city at the same time. They know what and where to see, which way to take, where the crowds are, at what time and where the famous dog is, whose nose everyone rubs to make a wish. Tourists go down to see its architecture and the metro becomes a museum for a moment. As Augé states that the metro: “draws us into quotidian humanity, the subway plays the role of a magnifying mirror that invites us to take account of a phenomenon that, without it, we might risk or perhaps try to be unaware of”(Auge and Conley, 2002). Moscow metro, as we established, has a relatively closed data cycle, where data collected in the metro is being used for

Project

proposal. Obesity case

improvement (in the best case) of transport efficiency of the metro. However, taking into consideration the above-mentioned importance of the metro for the city, not just as transport, but also as the biggest network of urban spaces and an inherent part of people’s experience of interaction with the city, such closeness doesn’t seem to be reasonable. Isolation /crowd, diversity/equality, density, ambiguity, dynamics, proximities, mobility pattern, social factors and area coverage - these characteristics of the metro could be turned into an opportunity of gathering huge amounts of well-organized and reliable data. Examples of data (Image 10) that could be collected there from people can vary from passenger traffic flow measurements to physical, biological and emotional states of the individual passengers. Use of the metro is inevitably tied with the interaction with technology, both direct (ticket validation, use of escalators, use of emergency call stands etc.) and indirect (being an object of surveillance by CCTV, for example). This, in fact, allows integrating data collection into regular routine of one’s trip. Moreover, such routine can become more pleasurable and amusing if methods of data gathering are designed in a way to make the process more interactive and, therefore, useful as an exchange of information, for example, or just to develop beneficial habits for passengers.

35


FRAMEWORK FOR DATA COLLECTION Data, which can be collected is very diverse, and is not really limited to numbers. Apart from quantitative data, we also propose to collect qualitative data about passengers. Metrics such as emotional state and behaviour patterns can give us valuable insights about the quality of urban environment and it’s impact on citizens’ well-being.

WHAT ARE WE LOOKING FOR

STRESS

DATA SOURCES & PRODUCERS

FACE: FACIAL EXPRESSION IRIS/RETINA OF EYE FACIAL

OBESITY

CHARACTERISTICS

BODY: INFLUENZA

SPEED OF WALKING POSTURE

SHIZOPHRENIA

GAIT PROXIMITY WEIGHT

SMOKING

HEIGHT EXTREMITIES BEHAVIORAL TRAITS

DRUG ADDICTION

TYPES & PARAMETERS OF DATA

BIO: PULSE OXYGENATION ELECTROCARDIOGRAM BRAIN ACTIVITY NERVE SYSTEM ACTIVITY GALVANIC SKIN RESPONSE GLUCOMETER SCALES VOICE TONE VOCAL TRACT PROPERTIES

POSITION: VELOCITY ACCELERATION MOVEMENT GLOBAL POSITIONING SYSTEM

BIO PROCESSES

ELECTROMAGNETIC ENVIRONMENT: CAPACITY

ALCOHOLISM

HANDS: PULSE SWEAT

CLOTHES

CONDUCTION MAGNETIC FIELD CHANGE CURRENT SENSING ELECTROMAGNETIC WAVES MEASUREMENT

FINGERPRINTS

HUMAN-SENSIBLE ENVIRONMENTAL ATTRIBUTES:

FRAGRANCE

VOICE: TONE PITCH

SMARTPHONE SMARTPHONE MODEL MODEL

LANGUAGE

SOUND WAVE AND SOUND PRESSURE BAROMETRIC PRESSURE HUMIDITY TEMPERATURE AIR MIXTURE PARTICLES IN THE AIR

TRAVEL PATTERNS

LUMINANCE

SMELL

LIQUID PRESSURE LIQUID PRESENCE

AGE

SKIN: COLOUR

GENDER

TEMPERATURE

INVISIBLE ENVIRONMENTAL CHARACTERISTICS: GAS MIXTURE GAS FLOW LIQUID MIXTURE

ENVIRONMENT LANGUAGE

OTHER

INVISIBLE LIGHT WAVES MEASUREMENT CAMERA SMART PHONES DETECTOR

RACE

SMART-CARD SCANNER SMARTPHONE

Image 10. Project

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proposal. Framework for data gathering

WIFI


According to ticket sales records, the majority of passengers travel regularly and, hence, compose a constant group of metro users that can be “tracked” over time. With mass introduction of smart-cards, they will most probably adopt the innovation and will readily contribute to the data. To ensure the efficiency on all stages of the process we propose to make the metro data as open as possible (taking into consideration the security aspect) so it can be used not only by official bodies but also by social activists and developers. Data collection, in fact, is just the first phase of the data cycle, which should be followed then by data mining, analysis and proper use of sensible outcome. This cycle can be illustrated with the following proposal, which we called “Weight measuring turnstile”. Problematics: Obesity has a negative impact, not just on one’s physical state, but it goes further, influencing the productivity of the workforce, their physical health and emotional state, and, hence, the economy of a city, given the position of Moscow as a capital (Maplecroft, 2013). It was not considered as a problem until very recently. Obesity Risk Index has published an article where they showed that Russia was rated the third country in the world, after Mexico and USA, where “current and emerging risks to business” are extremely high because of the obesity level increase. Moreover, together with other top-5 countries, Russia is “considered among the world’s most important regional markets and hosts significant labour forces utilised by many multinational companies”, which means that the economic impact of obesity spreads beyond country’s borders and goes global. Therefore, we see the urgency in addressing the problem of the emerging threat and awareness-raising among the general public, and the very first step should be the collection of proper data about the physical state of citizens. Based on the initial idea of using the metro as a ready-made infrastructure for collecting data from passengers, we assume that collection of data about metro passengers’ weight can be a suitable solution. Proposal (Image 9): By installing weight scales in every turnstile, the approximate weight of a passenger passing through it can be measured. It will be automatically compared to unique ID of a smart card, in order to avoid duplication of measurements. After collecting sufficient amount of data, it should be analyzed and visualized in relation to spatial structure of the city, and further on handed over to related authorities (Moscow Department of Healthcare and Russian Federal Ministry of Healthcare)

for the identification of problematic areas and possible decisions to be made. The second step in the process is continuous monitoring of obesity levels and the identification of positive or negative trends. Such monitoring can also help in the evaluation of measures, initiated by authorities. Another side of the process is an individual aspect of weight monitoring (Image 11). Weight is one of the most basic and physiological characteristics of the human body and, at the same time, an important indicator of one’s physical state. Integration of the process in everyday routine activity, such as commuting, makes it harder to avoid or forget about the procedure, which is a great benefit for a user. Existing smart-cards can be used as identifiers as well as storage media for keeping records and progress tracking. Moreover, the escalating popularity of the “quantified self” movement promises the recognition of the innovation, and will, potentially, increase the attractiveness of the metro as a public transport. As it was mentioned previously, the data, which can be collected, is very diverse, and is not really limited to numbers. Apart from quantitative data, we also propose to collect qualitative data about passengers. Metrics such as emotional state and behaviour patterns can give us valuable insights about quality of urban environment and its impact on citizens’ well-being. If we are to collect so much data from citizens (Image), there is a certain issue of data control and privacy. It is biopolitics, when transparency and openness rebound to the people. As Michel Foucault indicates, it is not possible to study the technologies of power without an analysis of the political rationality underpinning them, especially when the project is about breaking all rules of privacy, but it is a debatable question (Foucault, 2010). A generation of data generates power for those who have control over this data (Lemke, 2011). There are diverse and often conflicting views on evaluation of the biopolitics. Some argue that biopolitics is bound to rational decision-making and the democratic organization of social life, while others link the term to eugenics and racism, but the impact of bio technological innovations has demonstrated that life processes are transformable and controllable to an increasing degree (Lemke, 2011). The objects of biopolitics in a metro case are not singular human beings but their biological features measured and aggregated on the level of populations. This procedure makes it possible to define norms,

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establish standards, and determine average values. From this perspective, the notion of biopolitics refers to the emergence of a specific political knowledge and new disciplines, such as statistics, demography, epidemiology and biology. These disciplines make it possible to analyse processes of life on the level of populations and to govern individuals and collectives by practices of correction, exclusion and optimization. With this in mind, the realisation of the project proposal is meant to be controllable and considers relational and historical notions of biopolitics, privacy and control.

Nowadays, concepts of how data could be gathered make difference in obtaining knowledge. Existing methods of data collection such as observations, survey and statistics should be supplemented with user-generated data that generates real-time data actively. A combination of different types of data could add a great deal of depth to anthropological research, such as the research on Moscow Metro. Access to data such as user-generated content has reduced time spent for data collection, compared to gathering statistics from official sources, since, as it was stated previously, official data in Moscow is still unreliable and very much fragmented nowadays. However, certain specific skills and techniques are necessary for working with user-generated content and private data, such as biodata.

Nowadays, Google is one of the leaders in data collection, analysis, use and prediction. Google’s Data Sensing Lab has deployed 525 networked wireless sensors in San Francisco that detect five variables of air temperature and humidity, motion, noise level and infrared radiation (PIR sensor) every minute in real time (Fogarty, May 22, 2013), an experiment that went for quantity of data rather than variety. The Metro case could be a futuristic leader to compete with such giants as Google in data generation, variety of data sensory, value, provision and prediction of collective behaviour, physical, psychological, health and economical states.

It was also discovered that the visualisation of data plays an important role in knowledge generation. But beautiful infographics does not provide knowledge, unless there is a clear goal in understanding what you are looking for. However, this research has an exploratory nature and did not have a goal in finding solutions or a knowledge in data, but to identify potentials in work with various types of data, possible future outcomes, challenges and a concept of alternatives overall. In many situations, data will not eliminate the value of wisdom and intuition, but will make it more valuable by creating even greater uncertainty (Townsend et al., 2010). The experimental part of the research demonstrated the variety of data, which can be extracted from everyday urban experience, such as commuting by metro. This data consists of many layers, closely interconnected, thus has to be regarded in relation to each other. Some patterns were extracted from collected data, which point to the potentials it can offer.

c o n c l u s i o n Present research started with the general investigation of potentials of city data for urban planning (Image 12). We identified Moscow metro as a ready-to-be-used laboratory for collecting large amounts of urban data which can be used for many purposes from city management to application development, as it was demonstrated with examples.

Obviously explained methods have considerable limitations, which were taken into account. First of all, not all citizens use the metro, and, because of that, some social groups were underrepresented in the research. However, it is argued that metro

Image 11.

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Project

proposal.

Data gathering and processing


passengers still represent the majority of economically active population of Moscow, therefore can indicate general trends occurring in the city. Secondly, it is clear that presence of social media in the model of urban data has the considerable disadvantage of excluding certain social groups from comprehensive participation. In this respect, it is anticipated that use of mobile social services will very likely escalate in the near future and cover most of the social group. It is also worth mentioning that the penetration level of mobile internet in Moscow is more than twice the world’s average, and on top of that Moscow Metro has a great advantage of being fully covered with 3G network and having plans to be equipped with a free Wi-Fi network, which will definitely encourage passengers to go online. Today urban informatics is capable of sensing and responding to the events and activities transpiring around the city. Embedded technologies, imbued with the capacity to remember and correlate and anticipate, are envisioned as an active agent in everyday life for Muscovites and tourists. Novel technologies should unlock massive streams of data about cities and their residents. Based on this data, further analysis of many urban conditions, not even directly related to the metro or transportation, could be done. At the same time, we believe that focus should be not only on the collection of data, but also on how this data can be used. Every sensor, device, person, vehicle, building and street in urban areas can be used as a component to probe city dynamics to further enable citywide computing for coping with many urban challenges. It is important to understand, though, that on top of every technology there are people who make decisions. Even based on perfectly reliable data, they should be made by conscious and competent stakeholders and take into consideration many possible errors, context and, naturally, common sense.

r e f e r e n c e s Statistics in Moscow Metro ( ). [Online]. Available: http://www.brand-metro.ru/ [Accessed: 10/06/2013] Ac&M 2013. Cellular Data 2013. Advanced Communications & Media. Auge, M. & Conley, T. 2002. In the metro, U of Minnesota Press. Batty, M., Axhausen, K., Giannotti, F., Pozdnoukhov, A. & Bazzani, A. 2012. Smart cities of the future. Eur. Phys. J. Special Topics, 214, 481-518. Batty. M 2012. Smart cities, big data. Environment and Planning B: Planning and Design, 39, 191-193. Bruno, G. 2002. Atlas of Emotion (Journeys in Art, Architecture, and Film) Verso books.

Image 12. Data and aboveground

as a mediator between undeground

Carter, P. Dec 2012. Better Living through Information: Big Data and Urban Systems [Online]. Planetizen. Available: http://www.planetizen.com/node/59631 [Accessed: 10/06/2013] Cole, D. 1983. Sense and Sentience. SENSE5, 8/18/90. Cress, T. & Merriman, P. 2011. Geography of mobilities: practices, spaces, subjects, Ashgate Publishing. Diez-Roux & Ana, V. 2002. A glossary for multilevel analysis. Journal of Epidemiology and Community Health, 56, 588-594. Goodspeed, R. 2011. The Coming Urban Data Revolution. Available: http://www.planetizen.com/node/51158 [Accessed: 10/06/2013] Eaton, C., Deutsch, T., Deroos, D. & Lapis, G. 2012. Understanding Big Data. Analytics for enterprise class haddop and streaming data. Fogarty, K. May 22, 2013. Google’s Wireless Sensors: Big Data or Big Brother? Available: http://www. networkcomputing.com/wireless/googles-wireless-sensors-bigdata-or-big/240155347[Accessed: 10/06/2013] Foucault, M. 2010. The Birth of Biopolitics: Lectures at the Collège de France, 1978--1979 (Lectures at the College de France), Picador. Greenwood, V. 2012. Geoffrey West Finds the Physical Laws Embedded in Human Cities. Discover. The magazine of science, technology, and the future [Online]. Holl, S., Pallasmaa, J. & Perez-Gomez, A. 2007. Questions of Perception. Phenolenology of Architecture. , San Francisco, William Stout Publishers. Johnson 2013. Ericsson Mobility Report. Keene, T. The Apple Barrier: An Open Source Interface to the IPhone. Krylov, I. 2013. Device for measuring Bio and Environmental data [Online]. Available: https://github.com/igoraven/ arduino-biologger [Accessed]. Lemke, T. 2011. Biopolitics: An Advanced Introduction, NYU Press. Levine, R. 2006. A GEOGRAPHY OF TIME. The Temporal Misadventures of a Social Psychologist, or How Every Culture Keeps Time Just a Little Bit Differently. USA: Oneworld Publications. Montagu, A. 1986. Touching: The Human Significance of the Skin, New York. Nold, C. 2004. Emotional Cartography. Technologies of the Self, Creative Publisher. Nold, C. 2013. RE: Interview. Value of Data. Type to SHAKHBAZYAN, A. Mosmetro. May 2013. [Online]. Available: http://mosmetro.ru/ [Accessed: 10/06/2013] Maplecroft. 2013. Obesity Risk Index [Online]. Available: http://maplecroft.com/about/news/obesity_risk_index_2013. html [Accessed: 10/06/2013] Pallasmaa, J. 2005. The Eyes of the Skin: Architecture and the Senses. Pallasmaa, J. 2009. The thinking hand. Existential and Embodied Wisdom in Architecture. [Online].]. Priya, T. & Cresswell, T. 2008. Gendered mobilities, Ashgate Publishing Limited. Schwartz, R. 2012. Online Place Attachment: Exploring Technological Ties to Physical Places. Smith, C., Quercia, D. & Carpa, L. 2013. Finger on the pulse: identifying deprivation using transit flow analysis. In: Proceedings of the 2013 conference on Computer supported cooperative work, San Antonio, Texas, USA. Townsend, A., Maguire, R., Liebhold, M. & Crawford, M. 2010. A planet of civic laboratories. The future of cities, information, and inclusion.: Institute for the future. Watts, S. 2013. Will Big Data DNA analysis herald new era in medicine [Online]. Available: http://www.bbc.co.uk/news/ health-21045594 [Accessed: 10/06/2013] Wood, D. 2010. Lynch Debord: About Two Psychogeographies, USA.

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(R E) C H A R G E TOOLS E x p e r ie n c e o f r e f r a m in g t o ols u s e d f o r w o r k in g w it h d a t a & in f o r m a t io n Sergey Kasich

The true exploration is not to research something with tools we have, but to examine instruments themselves. Examples of researchbased “REcharging� of the tools is given in this report.

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in tr o d u c tio n The use of instruments once played a significant role in human evolution. That proto-human who used the tool made one step towards the future. That tool was a sign, a word - a mental instrument, which helped us to adapt to the world, but at the same time filtered it from the non-abstract mind of an animal. Just as our conciousness is dependant on words, information we have is dependant on tools, which we use to collect data, to process it and to represent. Just as any instrument is preprogram med to be used in a certain way - those tools program you on how to use them and, to some extent, what to get as a result. From methodology to tools. Let’s suggest a hierarchy from the highest level of abstraction in problem solving (as methodology) to the lowest (as tools). Despite that, knowledge about the city has been accumulated for more then two centuries already, there’s still no one distinctive methodology behind urban studies [4]. This gives researchers an opportunity to take any conception they like, as a basis for their design. In my case I suggest to use Wilhelm Windelband’s distinction between idiographic and nomothetic approaches to knowledge, to put the basic methodological differentiation as a starting point for the hierarchy [3]. [image 2] This distinction is highly effective in psychodiagnostics, where nomothetic ways of researching personality focus on generalizing features of individuals as a part of a group – thus making a general explanation theory. It researches differences of certain parameters inside the selection for comparison between subjects and enables the researcher to make typologies and classifications. It is ideographic – it is about individual case and uniqueness and it has no goal of structural comparison with selection. This way it doesn’t require separation of the object (individuality) to parameters (which is highly needed for nomothetic classification). These ways of research are complementary only. Nomothetic methods can be highly scientific, whereas ideographic ones are rarely accepted by general science, which is modeled after natural sciences, where the object is

always compared to physical or biological phenomena, which do not have all the layers com mon for human personality. [1, 3] I take psychodiagnostics as an example of a knowledge system which studies a highly complex object – human. It seems logically justified if we use this approach in studying the city for these reasons: 1) We take McLuhans way of thinking about the city as a prolongation of a human being 2) Referential urban researchers agree that the object of their study is too complex for being understood with quantitative and positivistic ways of study only. Different tools for different stages. The general algorithm of working with data and information has 3 main stages: gathering, processing, representation. The nature of a tool is procedural – as an instrument implacably contains the way of acting with it, because it was born for solving a particular problem [7]. That’s why it seems logically proven to classify tools, according to the stages of the process, in which they are involved. At the same time, some tools are really universal, or flexible enough to be useful in different stages. What data can we trust ? Usually data researchers have two opportunities: to work with existing databases (use secondary data), or to gather ones themselves (use primary data). Because the origins of secondary databases are not always clear, it of course can be trusted less. Although number of ways to examine databases validity exist, it is much safer to gather one by your own. And it is usually much more expensive. The price – is the price of the instrument. The relevance of data – is definitely the reason to (re)charge data tools. Data dependance on instrument (tool). According to a materialistic tradition I suggest deep dependence of the data produced on the tools being used. Most probably the preciseness of tool and competency of researcher (in his selection of object and subject) – are the main factors influencing the quality of data and research outcome. And if we talk about the methods and tools, which came to urban studies from other social sciences (as, for example, a questionnaire) there are ways to examine their precision. But if one were to talk about modern computerized

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and highly technological instruments – their construction is usually hidden from the researcher, who is acting as an enduser. At the same time such parameters as reliability and validity, or at least “level of absolute and relative error” should always be checked for any technology before it becomes a measuring tool. [11, 12] Can the researcher be the engineer? New types of instruments for new types of data. In the 21st century everyone can be an engineer (fabricator, maker) [8]. But it is, of course, not new. A lot of the existing theories were supported with methodologies and tools, invented from scratch, because new knowledge requires new approaches. And it is obvious that there are no professionals in something which has just appeared. New approaches can be evolved in order to prove an idea, or check the phenomena, but also can be done in an exploratory search of new fields of knowledge. At the same time, innovative findings can be done accidentally, or at least without a conscious purpose to find the new. Methodology of innovation: by-product of activities ( Y.A.Panamarev’s theory ). Error and Glitch as a by-product. One of the theories of creative thinking elaborates on the topic of the byproduct of problem solving as a source of innovation. It says, in general, that you can find an innovational solution to one problem, while solving completely another, if you’re sensitive enough and if your “unconsciousness” is engaged in searching the solution. This theory was experimentally proved by Russian psychologist Yakov Ponomarev at the end of the 20th century. [9] Interestingly enough, conceptually the same approach appeared in arts as a reaction to postmodernism. In its radical variant it is called the ‘Aesthetic of Falls’, and the digital version of it – Glitch. Glitch, the art-form, appeared as errors of all the previous art-forms. [10] The illustrative case study of this principle according to our topic is, for example, the project of German soundartist, Christina Kubisch. The “Electrical Walks” sound-art project accidentally becomes an instrument for researching city. People are given special devices (tools), such as the moded headphones, which can turn all the electromagnetic fields into

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Image 2. Methodology Model

sound. Then people are researching sound, walking through the street of the city. They listen to automatic doors, fridges, ATMs, etc. This is exploratory research. There’s a new tool and database, which exists as sound recordings, released on different labels. And this project has this kind of statistic on nearly 50 cities around the world. That was exactly an error (glitch) in electric scheme of a headphones, that led Kubisch to the invention of this concept in 80s. The “Electrical Walks Moscow” (which happened in May 2013) will be our case study on ReCharging Tools, by reframing the concept of data in the city in this project. DiY technique as a method for producing tools for urban research. So, now, when the artist can be an urban researcher, the urban researcher can be an engineer. It is called DiY – “do it yourself” approach. Initially elaborated in punk movement, it is now more associated with technological hacking and makercom munities. With the appearance of open software and such technologies as Arduino platform it became much easier for dilettantes to enter technology, and it is much cheaper. A number of hackspaces exist around the World already, and some of their projects are focused on urban studies. So this is the model to (re)charge the tool from it’s basics – invent your own. New tool = New data = New knowledge.


m e t h o d olo g y Study components [image 4] As the city is a very complex object to study we can actually develop a model, which will represent it in a simplified way, relevant to our subject. [image 5] The third part of our object of study is the process of working with information. We would take the model used by practicing data journalists (RIA novosti). [image 6] Framework Based on the models we’ve developed, let’s draw a framework which can be used as a basis to start the collection of a sample of tools. [image 7] We would suggest to start our collection of tools, using the “process” model, which is put into the nomothetic part, because it is clearly defined, so the tools can be put to the table and matched according their function. It seems that idiographic tools can also be put to the table, but they most probably will be matched in several parameters. The other option is to put idiographic tools into separate list. Anyway, the starting table for the collection was finally designed [image 9].

Practice: TAKING A SAMPLE Method 1) Make a list of stakeholders – actors in the city who work with data 2) Interview or survey them to find what they use for different stages of data work 3) Do a research in open sources, such as the internet and literature 4) Put everything into the table and match the tools according to parameters 5) Analyze the database and make a conclusion Providers of information: 1) City activists (Tepliza Socialnih Technologiy) 2) Research institutions (Levada Center, Center for the Study of New Media) 3) Business (research companies IPSOS , Consultant Plus) 4) Journalists (RIA news) 5) Open data activists (Information Culture company) 6) Academic urban research (Higher School of Urbanistics) The internet search as well as special literature was also used [13].

Image 5. City model

Image 4. Study components Image 6. Work with data - process model

Image 7. Framework

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160 140 120 100 80 60 40 20 0 general

gathering primary real gathering secondary gathering primary virtual storage

cleaning

analyzing qualitative representation other analyzing quantitative representation vizual

Image 9. the data base with a sample of 139 classified tools

Result We collected a sample of 139 items with data on name, description, developer, online/offline way of usage, open/not way of ownership and direct web url. All the items were checked on their availability and the data of the last check is also in the database. All the items were matched in 9 binary fields, according to the stages for which they can be used in a dataworking process – this was done on the basis of their official description as well as the answers of the experts, who use some of them. The direct url of the database published online is: http://tinyurl.com/plcn2wd [image 9]

a n alysis The simple quantitative representation of the parameters matched shows some significant gaps in the collected sample. [image 9. the graph] The nature of the sample dictates some of these gaps, but at the same time some of them might represent the situation in general. First, the gap between qualitative and quantitative analysis is com mon for any kind of research fields, because most of our research methodology is derived from natural sciences and driven by mathematics, which deals easily with quantities. At the same time qualitative methods are much more difficult to automatize. Tools, which can help with factorial and cluster analysis as well as tools for the analysis of social networks are matched in the qualitative column. Second, tools for the collection of primary virtual data (as, for example, some scrappers or aggregators) prevail over other collecting tools, because of

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the software-nature of most of the sample. So it is much easier for the software to collect something from the virtual space. To go to reality it needs sensors. At the same time, the only tool you need for searching the secondary data is a search engine. There are some specific search engines, EBSCOhost for example, focused on scientific data, but, in the end, it is just a searching engine. Third (and maybe most interesting) is the total victory of the visual representation of information. The thing is that there’s still no distinct way to represent data into any other modality, to make the information more clear for understanding. At the same time it is obvious that most of the significant information we, as human beings, get does not come from the eyes only. [7] Such applied fields with history, for more than 100 years as “sonification”, prove that well. The earliest example is the Geiger counter. So we would suggest to take two most significant gaps for further analysis and research.

Image 10. Difference in virtual versions of real Worlds by Yandex and Google


GAP: PRIMARY DATA COLLECTION TOOLS Proposal The most obvious software service which works with real physical space and virtualizes it is the interactive map. Such companies as Google and Yandex use their own sensory devices to scan the planet and make a virtual model of it. But if you’ll be able to find some differences in image 10 you’ll agree that we can’t trust these third party databases in everything. Yes, the virtual map is a secondary database, unless it is not made by yourself. And secondary data has twice as high a level of possible error than the primary one. But even if you’ll be able to produce your own tool to collect and digitize primary data, will it be the tool (the instrument)? Or will it be just a device (some working technical system)? The simplest digitizing is measurement. So we are talking about creating the measurement instrument. But what is the difference between ‘just some device’ and a measurement tool? Such a field of knowledge as Metrology gives the answer. The measurement instrument has it’s metrological characteristics. The first and the most simple ones are the level of errors: absolute and relative. So if we can build a device and then count at least it’s absolute and relative error we would be able to validate it’s measurement facilities and claim that it is a tool, but not just a technical system. Different measurement tools have different possible levels of error, with which they still can be regarded as tool, but not just device. If the error is higher – then the device can’t be used for measurement. Here’s the proposal for (re)charging this GAP of primary data collection tools: we should make our own simple and cheap device and then examine it’s errors, then we should claim that it be used as tool, or not. It is demonstrating the experiment which shows the procedure, which every data-researcher should pass if he wants to collect primary data with his own technical system. We call it… The (re)Counter Experiment As our goal in this experiment is formal and not related to concrete sphere of urban research, we decided to make the device for the first obvious physical process in the street – the pedestrian movement. So using the DiY techniques we produced a simple device to count pedestrians. [image 11]

1st series of the experiment Hypothesis We will be able to produce a technical system for measurement and examine it’s preciseness through counting absolute and relative errors. H1 – the error will show that the device can be used as measurement tool. H0 – the error will show, that the device can’t be used as a measurement tool. Scheme For the counting of errors we will need the empiric value (X) and true value (Y) of the measurement. For the (X) – we will take the value measured by the device. For the (Y) – the one measured by the validating agent, in our case a human, who will count the pedestrians in the same conditions, at the same time, as the device. The scheme of the ‘pilot’ and ‘actual’ takes of the experiment are shown in image 11. Calculating errors if X=empiric value , Y=true value absolute ERROR (XL) is counted by the expression: XL=X-Y relative ERROR (Ex) is counted by the expression: Ex=XL/Y * 100 (%) For the pilot take: X0=48 ; Y0=37 ; XL0=11 ; Ex0=29,7 (%) For the actual take: X1=295 ; Y1=226 ; XL1=69 ; Ex1=30,5 (%) Conclusion N1 The device has shown a level of relative error in two takes close to 30%. From a consultation with the developers of TrafficCom traffic measurement system we have the allowable level of error for traffic measurement devices. It is 5 %. As our device has the level of error close to 30% we can conclude that it can’t be used as a measurement tool. The H0 hypothesis is proved. But as we can see, the Ex0 is almost equal to Ex1. Let’s check the proportion: X0/X1=Ex0/Ex1 ; for example: X0/X1=Ex0/?? ??=182,5 which is not equal to Ex1. This also can show that there’s no proportion in growing values of the device measures and growth of the relative error. So we can assume that it stays stable at a level of 30% in different takes.

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It means that the device can’t be used in measurement of absolute values in interval scale (finding an exact quantity of passed pedestrians), but probably it can be used in relative measurements in order scale (comparing the flow of pedestrians in terms of “more at this period of time \ less at this period of time”) [14] 2nd series of the experiment Hypothesis We will put the device to field conditions for a period of time, enough to be sure about fluctuations in pedestrian flow. H1 – the values measured by the tool will show fluctuation close to the assumed one. H0 – the values of the tool will not show fluctuation close to the assumed one. Scheme We put the device to the field for more then 12 hours and leave it to work autonomously. We start the take at 6 a.m. 24.05.13 and finish it at 10 p.m. of the same day. We assume that the flow of pedestrians will be low until the time when people start to go for work – so in the period of 8-11 a.m. we assume the growth of the value. Then we assume that it will go down for some hours in the middle of the day, and will start to grow again by the 17-18 hours, as people will get back from the dayjob. We would assume the further growth of the activity of the pass, because of the public event, which is expected near the place of measurement in the night. [image 12, graph 1] Analysis We put the device at 6 a.m. in the morning, but the first time we checked it – at 10 a.m. – it was found laying down near the place of installation. Therefore we can’t trust the data collected from 6 to 10.7 a.m. This data shows that it was counting till 6.49 and then stopped. That probably was the time it fell down. The first explanation we thought about was, of course, vandalism. But the tool was safe, and it was working, but not measuring, because the sensor was not exposed to the area. Funnily enough, later that morning of 24th of May all the news was about the earthquake in Moscow, which happened with several hits in the morning exactly at that period of time. So probably the device “counted” the earthquake. Finally we had values for 12 full hours: from 10 a.m. to 10 p.m.

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Our measured field seems to be very engaged. There’s almost no minute during the day that it is not passed by someone, according to our device. The chart with values of average triggers per minute shows almost noise with the near stable value of an average 10 triggers per minute (which we should not count as the number of pedestrians, according to our first series) (image 12, graph 2). It also shows a distinctive decay between 13 and 15-16 hours. The chart with sum marized triggers per hour is less messy (image 12, graph 3). It clearly shows the fluctuation which is more or less close to the assumed one. Conclusion N2 We can declare that the H1 hypothesis is proved in this stage. But we still want to see much more distinctive fluctuation. It should be much obvious, if we could put the device for the night and then see the transition from night triggers to the day ones. 3rd series of the experiment Hypothesis We will put the device to field conditions at night time and then take it back at day time. H1 – the values measured by the tool will show a clear transition from night time to the day time. H0 – the values measured by the tool will not show clear transition from night time to the daytime. Scheme The scheme in this series is the same as the previous one, except the time. We put the device at 4.23 a.m. of 26.05.13 and take it away at about 4 p.m. Analysis Unfortunately, the time of the start of this series of the experiment was the last time we saw the tool (image 13). It is sad that the person who took it away didn’t even call us, because the device was matched with a phone number and sign reading “please do not move”. The (re)Counter Experiment conclusion proved that it is possible to make your own simple and cheap technical system for digitizing physical process in urban space (collecting physical primary data). We also proved that it is possible to count it’s simple metrology characteristics as levels


of errors and find the usage of the tool according to it’s precision. We also proved that people in Moscow are not afraid of strange technical objects and ready to take them away, without even giving a phone call to the owner.

GAP: PRIMARY DATA COLLECTION TOOLS + NONVISUAL REPRESENTATION Proposal The most distinctive gap found in our analysis of the sample (image 9) is socalled “visual dictatorship”. We can agree that the most useful way of representing data is via visual modality: about 80% of useful information a human gets with his eyes. At the same time, we have the remaining 20%. And let’s not forget about the 285 million people who are blind (WHO Fact Sheet N°282, June 2012). For them, the data, represented visually, just doesn’t exist. Moreover, there are situations in which the visualization of the data is less efficient: makes the system too complex, more expensive\difficult to produce. The Geiger counter or the metal detector, or sonar – are the examples. The sonification usually signalizes binary events, or shows the data in order scale (closer to smthng, further from smthng). Also, it is usually the real-time representation. So the process of collection is the process of representation. Despite the practicallyoriented usage of sonification, it also can be used for the research in a less positivistic way. The sound itself can create spaces for the listener. So, for example, in the conditions of spatial exploration, representation in sound can create the parallel model of the environment. At the same time, sound is a dynamic experience. And it is another type of dynamics than the looking over of a picture. The statics can turn into process thanks to representation in sound. This experience itself seems to be fascinating for people. And probably it can add a new angle to the exploration of phenomena. Will it influence people at all? Let’s find an example of a tool (not so usual as the Geiger counter), which works with urban data and represents it as sound, and research it as a case study. It obviously can be a good “(re)charging of urban tools”, if: 1) the tool will be new in general; 2) or if it will be new to the conditions in which we will use it.

Case Study: Electrical Walks Moscow The Exhibition “Sensing Place” happened in Basel (Germany) in 2012, gathered a bunch of the most interesting media-art projects in fields of spatial-oriented approach. [15] One of the most famous spatial sound-art projects – Electrical Walks by Christina Kubisch (Berlin) – also was presented there. The Electrical Walks started in 2003 as Christina accidentally found out that the specially modified headphones, which she used to use in her gallery works, were permanently catching non-expected sounds from the environment. The sounds appeared to be the electromagnetic emitting, which does exist in a form of fields in the urban environment, as an invisible shadow of all electric processes. Since then the supersuccessful art-project entered 45 cities all over the World. It was held in Paris, Barcelona, New-York, London, Mexico among others. In all these cities people were given special headphones, which let them hear all the electromagnetic fields in the air. With a special map people then could walk through the city and explore the sounds of electricity alive. In February 2013 we visited Berlin and had an interview with Christina. She admitted that she never perceived her project as a tool for urban research, but more as a non-standard sound experience. At the same time she likes the research nature of the system and scenario of the project, which stimulates people to behave in an explorative way and become curious. So the main purpose of Electrical Walks is to give people the unique experience of “feeling” this kind of spatial data (the level of electromagnetic fields in a city). It is not about measuring, but more about living through it. So the only way to make a real case study with the project is to go through it and let the citizens go through it. That’s why we brought the Electrical Walks to Moscow. From 8th of May 2013 till 29th of May 2013 this project, for the first time in its history, happened in Russia (image 15). The attendance was absolutely free during all three weeks. We also made a promotion of the project to invite Muscovites. Three governmental organizations helped to bring Christina and her famous headphones to Moscow: Guethe Institute Moscow, National Center for Contemporary Arts and Skryabin Museum. 395 people registered to visit the walks. More than 100 actually visited during 15 full days of the project.

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Experiment If perceiving the walks as an original tool for idiographic exploration of the city, the main and the only study that can be made is just your experience of this spatial electric sound. So, giving the opportunity to anyone who wants to have this experience, we already completed the goal of the study. But it is interesting to try some positivistic methods to find out something new about this tool. Let’s take two samples of people: Ep – experimental sample - ones, who have passed through the Walks in Moscow. Cp – control sample – ones who don’t know about this project at all, so we elaborated the hypothesis. Hypothesis We want to find out how the experience of the walk really influences on citizen. H0 – Ep will give less value to the factor of electromagnetic fields among other ecological urban factors, in comparison with Cp. H1 - Ep will give more value to the factor of electromagnetic fields among other ecological urban factors, in comparison with Cp. Hn – the reactions of Ep and Cp will be similar. Scheme We designed two surveys with the same number of 9 ecological urban factors and the same 5-point scales. The N21 survey had two entrance questions about the experience of Electrical Walks in Moscow, and was given to people who had passed the project (usually right after their return). The N23 survey had no entrance questions and just proposed the same scales with the same 9 factors as N21. The factors were always in the same order and had a prepending text: “Imagine that you want to live in a new district. There are several factors which can help you in your choice of a new place to live. Please evaluate them according to the level of importance for you personally. Distance to the park or green zone Transport infrastructure Level of noise in a district Radioactivity level Level of electromagnetic fields Distance to sport venues Quality of air and water Distance to the nearest natural or artificial water pool Distance to the nearest supermarket

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Results We collected 42 answers for the survey N21 (Ep) and 46 for the survey N23 (Cp). The 8 scales are actually masking the one in which we are interested - the factor of electromagnetic fields (5th question). Calculating Counted average: N21average=2,762 ; N23average=3,283 The accumulated frequencies of the scores are shown in image 15. We can see that the average raw score for the parameter in the Cp sample is higher than in Ep. Pearson X-squared test showed that the difference in the two distributions is statistically insignificant. We would treat it as a sign that two samples are balanced. And if the amount of participants is also similar we can try to apply the Sign Test (G) to see if we can trust the shift in the parameter. We take only 42 items from the larger sample and use the Sign Test (G) for the both results. The G-test shows that the shift in the parameter is statistically significant with the level of 0,01. Conclusion We can claim that the people who passed through Electrical Walks Moscow pay less value to the factor of electromagnetic fields than the people who have no idea about the project. We can claim that the H0 hypothesis is proved. Post-Analysis Surprisingly, it seems that, if you had the opportunity to listen to the electromagnetic fields, then this factor becomes less significant to you. Or maybe we can treat it as the factor becoming less scary. The people who didn’t listen to the electromagnetic fields probably had no interest in thinking about what it was. So, when they get the question about the electromagnetic waves near the question about radioactivity, they probably rate it higher, because of the fear of unknown. Indirectly our result is proved by the behavioral therapy of fears, in which it is com mon knowledge that the more you know about the fear-factor, the less it frightens you.

The Electrical Walks Moscow Case Study conclusion The feedback (collected with the entrance questions in N21 survey) about the project, in general, is positive. People feel engaged and curious, despite that the


sound is sometimes hard to listen to. And also, as our experiment showed, people get influenced by what they listen to. Before the actual start of the project, Christina Kubisch herself was exploring Moscow in preparation of the public part. Here are some empirical findings, which she mentioned in interview, comparing Moscow to other cities: 1) Moscow is a very loud city. I can compare it to Mexico only. The level of noise on the streets is even higher than the loudness of electromagnetic sounds, which are also quite loud. 2) It is the first time I actually caught radio broadcast so often. You can hear some radio during all Old Arbat street actually. It means that the radio station transmitter is somewhere near and it is very powerful, because the phones do not work with radio frequencies. 3) You have a lot of different Banks here. I’ve never seen such an amount of different ATMs in one place. It is like bankomat-street. The fact is that all the bankomats sound differently – that’s very interesting. 4) The security gates in the entrances to some shops (e.g. the Moscow Book House at New Arbat) are extremely loud. They are so loud, that you can damage your ears. Usually it means that the owner tries to do economically on making the magnetic marks on the goods smaller in size. It is cheaper to do them smaller and just switch you security gates with more power. It is prohibited in some countries because such levels of magnetic emitting can damage, for example, cardiostimulator or any other fragile equipment. 5) The low tone of the electric wires is also very often heard here – they are under the ground, but close to the surface in this area. 6) Some strange signals emitted by antennas near the Ministry of International Affairs. 7) Very nice you can hear GPS signals of cars passing over your head, when you’re in the underpass. 8) The Metro makes good sound usually, when the train starts, or stops. In general, it sounds very nice even without the headphones. But it is also very loud.

General conclusion and some by-products In this project we examined the existing tools used to work with data and information in general and in urban research. We made a working classification and collected a sample of 139 tools. Our analysis showed distinctive gaps in the collection, perhaps representing the gaps in general. So we made experimental studies, showing the way to (re)charge tools and fill in these gaps. First, we showed the way, how everyone nowadays can make his own tool for primary data collection and validate it with basic metrology parameters. Second, we introduced Moscow to the unique way of experiencing one of its hidden layers - electromagnetic fields - using a special tool for primary data collection and representing it in sound. We experimentally showed that this reframing experience does influence people’s behavior and future decisions significantly. Some of the by-products of this study are presented in image 16.

r e fer e n c e s

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Power source 5v RTC clock module PIR movement sensor

Pilot Take experimental scheme

Actual Take experimental scheme

pedestrian pedestrian device

observer

observer

device observer observer

1) date: 19-05-13 ; 2) time interval: from 23-20 to 23-40 3) number of observers: 1 4) measured by device X0=48; measured by observer Y0=37; absolute error XL0=11; relative error Ex0=29,7(%)

Metric 3mm Linear Blue MC - Port Letter

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1) we invite two independant people to be observers 2) the two go through the Landolt’s test - to check their level of attention and activation 3) all observers match their clocks 4) observers take their positions 5) device is hidden in camouflage, 6) experiment starts 7) date: 22-05-13 ; time: from 12-40 to 13-40 8) the Y1 data is counted as an average between the counts of all three observers (Ya, Yb, Yc) 9) X1=295; Y1=226; XL1=69; Ex1=30.5(%)

http://customgraph.com


Arduino Nano microcontroller

Image 11. The device & first series of experiment SD memory card

Metric 3mm Linear Blue MC - Port Letter

http://customgraph.com

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Image 12. Second series of experiment Scheme

Graph 1. The assumed pedestrian flow

15 hours

amount

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4) start at 6.24 am ; 24.05.13

Graph 2. Triggers per minute fluctuation for 12 hours

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assumed fluctuation from 10am

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Metric 3mm Linear Blue MC - Port Letter

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Custom Graph™ Image 13. Third series of experiment Scheme

The assumed pedestrian flow

15 hours

pedestrian device 4

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2) setting up at the place 3) start 4:23 am, 26.05.13

3) at 11:11 tool was not found

Metric 3mm Linear Blue MC - Port Letter

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image 15. Electrical Walks Moscow special headphones

Christina Kubisch

map for the Walks (Arbat)

Buklets

average 23 average average2321 average 21

+a/ +a/ scores

F

scores

Criterion analysis

FSUM 8

8 8

average 23 average average2321 average 21 average 23 average average2321 average 21

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k

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average 23 average average2321 average 21

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average 23 average average2321 average 21 88

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average 23 average average2321 average 21 scores

X

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image 16. by-products

The sample of tools we collected for the study has became a starting point for the open renewable and addable base of tools for the data-researchers, which is now in development. Here’s the pilot interface, produced in collaboration with Teplitsa of Social Technologies.

We worked with the pedestrians counter technology. Use of the IR sensors is not the most precise way to do that. There are some more approaches. But in general what if we could combine the concept of sonification, elaborated in our case study and the counting? At least it can be an engaging art-project. And now we know that these kind of projects can really have the influence on people. “The Quiet Spot project” “Moscow is so loud” - said Christina Kubisch. What if we could measure the DBs in the city and find the most quiet places? We can do it as project for public spaces, e.g. parks. Then we can put some nicely designed anechoic walls in the place, still leaving it open to sky and nature. Thus the citizens will know exactly where to find silence in the city.

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C HIL D R E N G E N E R AT E D D ATA I s w a s t ela n d a  pla y g r o u n d ? by Oxana Yatsenko

ÂŤThe

lives

become

much

of

children

more

have

restricted

and controlled over the last 30 years or so. Hence, for many children today, playgrounds are amongst the few spaces that can offer

interesting,

challenging

opportunities for play. Children want and need to have challenging play

experience

that

involves

a degree of managed riskÂť Tim Gill, Play England

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Limbo game

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in tr o d u c tio n Children’s environment – brief description Each city can be measured by a huge amount of criteria to identify if it is a children friendly one. Canadian cities are on the first rank on it. Rotterdam is trying hard to make the situation better, they have government program towards making the town more safe and intere>sting for children. There is a huge amount of activist movement.(Marguerite van den Berg, 2012) The first time the discussion about it arose in Russia was during the 2nd Moscow Urban Forum. In Moscow, according to registry office, 125 058 births were registered in 2011, and this number is bigger by 1420 than in 2010. 2011 was the first time during the last 23 when births exceeded deaths. 135 000 children were born in 2012. (Report about children condition and families, who have children in Moscow ) In spite of these numbers, people continue to say that when we observe the city environment we notice that there are no children. Almost all mothers recognize some of the diverse benefits of outdoor play, but obstacles, such as television, computers, and concerns about crime, safety, and injury, prevented their children from participating in more outdoor play. The others say that there is a demographic crisis, that is why there are no children around. With this research I decided to check if they are outdoors or not, and what kind of places they like to spend time in. Examining how children spend their time can tell us a great deal about their lives, what parents and society value, and what changes may be occurring over different generations. Today’s young children appear to have a more restricted range in which they can play freely, have fewer playmates, and, in many cases, their friends are less diverse. (Karsten, 2005). I decided to research environment through children generated data, trying to understand how information can be reached out and analyzed in order to use it for making childrens’ environment better, to see the problems

which children meet and to seize which steps should be undertaken to identify places of high children importance. Children generated data can help to diagnose such places and give a clue towards the future methodology of their identification.

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his t o r ic al o b s er vatio n To trace the history of the creation of socalled “yard” sites is rather complicated, but still the first playground appeared in 1909 in Moscow with the support of community “Child labor and leisure”, which was responsible for games and entertainment.In 1912, the number of playgrounds has grown to 24.Sports entered the lives of people in the Russian pre-revolutionary years, starting the craze in football and tennis, and sports fields were built for the first time. In Soviet Russia the construction of playgrounds and sports fields developed very rapidly. In the 1920s to 1940s centers for young naturalists, children’s railroads and flotillas were built. There were children’s suburban pioneer camps with the extensive complexes directly for a child’s development in the countryside. Pre-war and post-war years brought airplanes, small tanks, ships, where the children played happily in the “voynushku” on the playgrounds . Control of pre-schools and parks were undertaken by public education.In the 50-60th there were parks and leisure centers, children’s camps. Quantitative and qualitative growth of institutions for the organization of further education, including children’s playgrounds, happened. Participation in the organization of children’s leisure was taken almost by all departments. During the period of the collapse of the Soviet Union in the 1990s, due to lack of funding and attention, some sites became worthlessness. These years were characterized by the decline and lack of attention in the development of education. There are special playgrounds, parks and, of course, there are still natural open spaces and streets. Kids had to be entertained and be strong physically, while parents had been working for the good of communism. The kindergartens appeared already in the 1930s and it was one of the typical feature of soviet epoch. The state decided to relieve women partly from the children care in order to allow them to spend more time at work. There are not so many alternatives for children right now. Most of the playgrounds are ordered from the Scandinavian countries. As an architect Ilya Mukosey says, they are the cheapest and are in popular demand due to the scandinavian research. That is why we have quite typical playgrounds which are sometimes left without any attention and children prefer the near surrounding to the yellow-red stamp playgrounds. The other reason why the playgrounds are alike is that it is difficult to get certification for new kind of inventory. Usually it is only the client who cares about the


Image 1. Child in the construction area

Image 2. Empty closed playground in Bagrationovskiy micro-district

beauty, so the playground planners propose the elements for the client. So it is him who will say how the playgrounds should look like. There is not much challenge on the Moscow market in the sphere of playgrounds for now.

By the mighty children environment I mean the place, where children spend the most of their time, where they like to come back, where they feel themselves free, safe and fun. Sometimes you can meet some artifacts left there. There is such a science as an ethology – morphology of animal and people behavior. Mark - in the science of animal behavior (ethology) – a sign which is left on the objects for the purpose of communication. The same things happen with children when they leave some things in the environment. They say that it is their place and they are comfortable to play there.

Children’s environment deeply depends on the the parent’s behavior towards it. Parents make rules letting or not letting their children go outside. Press, mass-media, government and schools make us fear to let our children go outside, because there is a stranger danger there. “Don’t speak with people, don’t go there, don’t play in puddles” - that is what you usually hear from adults. American writer Leonore, the author of free range kids told me how American families are keen on controlling children’s space for 24/7. Kid’s product chips are in high demand nowadays. Now you can go tracking your child. Advertising all around makes you believe that without this or that gadget your child will never start to walk or if he starts doing it without its help, he will die. “American parents go to the extremes if we talk about the children bringing up,” - says Lenore. They buy a lot of products which actually they don’t need. While doing it they narrow down the environment as much as possible.

Natural space is an alternative to the playgrounds, because there are challenging play opportunities. Children themselves have an option about what to do on the open space. They can play hide-and-seek, jump, run, play with the ball, have a picnic, make acrobatic exercises or to be on their own. Open not built environment doesn’t seem dull or boring to them because the micro districts are filled with playgrounds and there is not as much of a place to run and there is always road danger.

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Anya,Anya, 8 years 8 yearsold old Spends all seasons at BagraSpends all seasons at tionovski wasteland

Bagrationovski wasteland

Alina, 14 years old Alina, 14 years old Use the whole territory whole territory. WantsUsetotheplace benches Wants to place benches

Alexander, 16 years Alexander, 16 yearsold old walks with small Walks his with his smallbrother brother. Use theUse garage territory the garage territory

Nastya, 17 years Nastya, 17 yearsold old Walking her dog with boyfriend

Walking her dog with her boyfriend Image 3. Understanding of the borders of the wasteland and meaning of the place by children.

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m e t h o d olo g y

a n alysis

My case - study of the research is Bagrationovskiy wasteland near Bagrationovskaya station. I chose it because of several reasons. One of the reasons – it is a part of the first stage of the territory planning project which proposing to build a cultural and education area of 0.4 hectares with a modular Orthodox church with the capaciousness for 300 people with parish house there. In the second stage it is proposed to build a housing and public utilities area of 0.82 hectares and a multi-level garage complex height of 9 floors plus underground with the capaciousness for 1,023 parking places with a built-in object of civil defense and land a temporary parking place for 25 cars. (invest. mos.ru )

Observing the environment we can say if it is a good place or bad by counting what age is presented there. You may say that it is really a good place if there are children from birth to adults age. I made several surveys on open green space of Bagrationovskaya. One is interviewing children and playing with them there. Like this I have got the idea of how they use the place. Most of children run there and scream, pick up flowers, play with grass and trees, play with dogs. 100 % of those interrogated answered that they come here every day in winter because it is beautiful and the hills are covered with snow. There are several natural slides. You can ski, slide, snowboard there. And this place is unique because children of all ages come and enjoy it, even from other micro-districts. Children of 12 years old told that they come here when they want to be alone, because it is the only place where they can be without parents. From the other side, it is a great place for meetings with friends. The survey showed that it is the most important factor of the favorite place.

The other important thing that this is an entertainment place for children and it is popular in all seasons. I am observing this place through different layers of information, and one of the most important is children generated data, because we obviously used to talk to all people except the minorities, our children. I am getting data through children interviews, mapping, drawings, observation, twitter, internet survey plus phototracking. I have tried to focus on different methods of looking at data, as already verified data, so and new techniques. I started with children interviews in-person and observation of wasteland and playgrounds around, trying to understand what children like or don’t like about the environment. What is there favorite place to play? How much time do they spend there? What do they do there? I continued to ask adults and I noticed that I get quite different answers ,sometimes, on the same questions. That is why I launched an Internet survey with more optional questions in order to see how the children and adult perception of the environment around us differs. I placed it in vkontakte because there are a lot of teenagers who use it. The parent’s questionnaire was downloaded in different family groups. Content Analyses: qualitative data from the open‐ended questionnaire items were analyzed for patterns and themes. Descriptive Statistics: frequencies, means and percentages were calculated for each questionnaire item.

There is Filevskiy Park there, but it is quite far, that is why this green island is so popular among all ages. This micro-district has plenty of playgrounds, but children say that it is their favorite one, because parents don’t disturb. Parents say a lot of ‘no’ on the playgrounds. Don’t do this, don’t run on the road. And this place is safe and big. So, you can play the fool without limits. There is one playground which is always occupied with alcoholics, so 100% of those interrogated said that they are never there. There are two more, which are heavily used. There is a school playground, but it is old, so all pupils occupy the nearby playgrounds, that is why sometimes there is no place for the small children. Another playground, behind the school is situated under the sun, so parents forbid to play there because of the threat to get a sunstroke. There were other interesting things discovered due to the survey: that there is more place for cars and too many roads in this place for children play. The launched Internet survey showed that children favorite places in Moscow are fountains, with animals, where the other children are, open green islands. If to look more precise 39% chose open spaces and park zones, 36,5 % - playgounds, 12,2 % - places with animals, 2, 43% — forest.

I have tried to understand what kind of people live near Bagrationovskiy wasteland through twitter and foursquare check - ins. Through the photo stream I analyzed how children use the field. Drawings and mapping showed their favorite wasteland objects and the borders of their private space there.

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children kids zone

family family zone adults adult motion kids motion family motion dog walking

Image 3. Mapping of people motion in Bagrationovskaya wasteland, the 30th of June, 2013

foto by Anton Zabrodin, near New Jerusalem

Image 4. Development plan of Bagrationovskaya wasteland, 2012 The Moscow City Committee of investment projects implementation in construction and control of shared construction.

c o n clu sio n s Observations and surveys showed that sometimes new three – colored playgrounds are not the best remedies for getting children out. It turned out that that they prefer wastelands to playground. Even though it is not a managed park, it is without light and benches. The interesting thing is that 54% of parents said that they prefer their children to play on the playgrounds, while 90% children voted for the wastelands.

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Children have an intricate knowledge of their local community and consider the quality of their local environment to be of great importance. Children’s knowledge of their local community and ideas to improve their environment are not included in the school curriculum. However, children feel strongly that their schools should support them in achieving their goals.


Image 5. Photo by Anton Zabrodin, near New Jerusalem

p r oje c t p r o p o s al Planning practice is an interactive process that generally involves many stakeholders. In order to make formative decisions and implement them, government, businesses, and citizens work to address local and regional issues. Despite the widespread involvement of stakeholder groups, one faction is consistently ignored in planning decisions: children. In the push to make decisions and consider the numerous viewpoints of the adult population, children are habitually left by the wayside. Planners all too often fail to acknowledge that local children may have insightful and creative ideas to address issues. This is particularly true when these issues affect the local children, as is often the case with environmental planning decisions. How can planners incorporate children in the practice of environmental planning? Planners and educators have a unique opportunity to become part of a movement to incorporate children in environmental stewardship. By using environmental education to create a basis of knowledge about local issues and to provide a platform for children’s participation, their ideas can be incorporated into planning.

Image 6. Photo

by Anton Zabrodin, Park of the 50th anniversary of Oktyabrya

r e fer e n c e s

Beldon Russonello and Stewart Research and Communications, 2003 Bruck et al.,1998, Complex Issues in Child Custody Evaluations Claveirole Anne, 2004, Listening to young voices: challenges of research with adolescent mental health service users. Deatrick J. A. & Ledlie S. W., 2000, Interviewing Young Children: Explicating Our Practices and Dilemmas Holly Grason, 1995, RETHINKING THE ORGANIZATION OF CHILDREN’S PROGRAMS: LESSONS FROM THE ELDERLY Howard Frumkin and Richard Louv, 2005. From “The Powerful Link between Conserving Land and Preserving Human Health:” http://atfiles.org/files/pdf/FrumkinLouv.pdf Kellert, Stephen R. “Nature and Childhood Development.” In Building for Life: Designing and Understanding the Human-Nature Connection. Washington, D.C.: Island Press, 2005. Lenore Skenazy, 2010, «Free range kids» Marguerite van den Berg, 2012 «City Children and Genderfied Neighbourhoods: The New Generation as Urban Regeneration Strategy.» Melanie Mauthner, 1997, Methodological aspects of collecting data from children: lessons from three research projects, http://onlinelibrary.wiley.com/doi/10.1111/j.1099-0860.1997. tb00003.x/abstract Rew et al., 2004; «Watson et al., 2001» Robert Goodman , Stephen Scott, 1997, Child Psychiatry, Blackwell Science. Sheldon Cohen; Thomas A. Wills, 1985, «Stress, social support, and the buffering hypothesis» Tim Gill, 2010, «Play England « Centers for Disease Control and Prevention, 2006, Centers for Disease Control and Prevention, 2006

I propose to create a toolkit of wasteland identification as an important place for their users, or not, in order not to damage the environment. -

Observation Internet survey Phototracking Interviews Mapping Tweets,foursquare, instagram Semantic analysis Quantative analysis To involve children in decision making

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MOSCOW DIS T R IC T S ID “ R e g io n al s y n d r o m e ” a n d p a r t ic ip a t o r y c it y in d e x Maria Romakina

MOSCOW IS AN “ALLIANCE” OF 125 DISTRICTS, WHICH ARE GROUPED INTO BIGGER

SPATIAL-ADMINISTRATIVE

UNITS - OKRUGS. WHAT IF WE WILL DEFINE URBAN CHARACTER OF EACH DISTRICT SOCIAL

DATA?

SOMETHING SPACE?

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WITH

NEW

MACRODATA

WILL

WE

ABOUT

AND

DISCOVER THE

CITY


al area, %

density, residental area, %1000 citizens/ha

l area, %

average $/m2 industrial area, price, %

n zone, %

green zones, % m2/capita living

water, %

roads, %

people, %

educated school, %

%

water, % rub. of municipal budget/capita

roads, % chairs in hairdressing salons/1000 citizens

places people, in schools/1000 citizens higly educated %

currentlyplaces being in educated in the citizens hospitals/1000 middle school, %

density, 1000 citizens/ha

%

average price, $/m2

%

living m2/capita

%

rub. of municipal budget/capita

%

chairs in hairdressing salons/1000 citizens

%

places in schools/1000 citizens

d %

places in hospitals/1000 citizens

Image 1. Results of applying the Regional Syndrome methodology to Moscow city space, floating cortege of 3 characteristics

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f u n c t i o n a l

z o n i n g

o f

%

%

69-86 53-69 36-53 20-36

38-47 28-38 19-28 9-19

4-20 N/D

0-9 N/D

Image 2. Residental zones, % The most saturated: Zyuzino, Lomonosovsky, Beskudnikovsky, Arbat

Image 3. Industrical zones, % The most industrial ones: Pechatniki, Kapotnya, Vostochny, Nijegorodsky, Danilovsky

%

% 68-85 51-68 34-51 17-34

16-21 12-16 8-12 4-8

0-17 N/D

0-4 N/D

Image 4. Greenery, % The most green: Metrogorodok, Yasenevo, Izmailovo, Sokolniki

m o s c o w

Image 5. Water, % Richest by water: Strogino, Pechatniki, Khoroshevo-Mnevniki, Nagatinsky zaton, Krylatskoe

The first open-source attempt to get statistical information about functional zones in Moscow districts. Information has been scrapped from OpenStreetMap by ArcGis. Innacuracy is minimal, relative to the accuracy of OpenStreetMap. This crowdsoursing map has shown much more precise results than the official generalized Genplan-2025 map.

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in tr o d u c tio n This research has been conducted following the changes of recent months: Moscow has started a new period of its existence – an era of open data (symbolically, as a starting point, we might estimate the appearance of a branch of web-sites, opened by Moscow government in january 2013 around www.data. mos.ru). At the same time, during the last years and decades we could observe the prosesses of restructuring the post-soviet territories, as well as observe an increasing sense of spatiality. During soviet times USSR people were characterized by aspatiality (Smirnyagin). A good illustration for that - a quote from a soviet song: “Moi adres ne dom i ne ulitsa, moi adres - Sovetsky Soyuz (My address is not my house or my street, my address is - USSR).” Socio-econimical changes in postsoviet times started up the prosesses of territorial differentiation: the tendency for unification and reducing the diversity has been replaced by economically driven territorial segregation of population. The main focus of this research is an attepmt to read the territorial differentiation of modern Moscow by the use of different types of data: 1) official and commercial statistics, provided by Mosgorstat, Municipal Councils, www.data.mos.ru, Census Institute and IRN.RU 2) map information from Genplan-2025 map, Kadastr map, OpenStreetMap 3) results of the survey, made by the author of this research in may 2013, 4) social media data (Twitter). The initial idea is to combine macroscale and microscale level of reading and analyzing the city for a branch of purposes: defining urban characters of all districts and building a typology of them (as a first step for building an index), verifying “common opinions” by means of data (it is obvious that the liveability status of Zamoskvorechie is higher than of Golyanovo, but can we prove that by unemotional numbers?), getting the subjective picture of popularity of districts between citizens and a picture of mobility within the districts. An indexing system of districts might be useful from different prospectives. It might help citizens to navigate the city environment in everyday practices or at the moment of the “big decision” (choosing a place to live or to work). It might help commercial companies to run their businesses and fulfill lacunes in different districts and other stakeholders as well. For example: can urban planners ascertain the local identity and use this knowleadge for planning? Or: might cultural policy based on the territorial differentiation be more local and how? City index might be helpful for authorities as an information instrument which indicates socio-economical and other processes in the city.

m e t h o d olo g y Territorial identity is a complex category which includes different components or subcategories – landscape-ecological, architectural, infrastructural, socioeconomical, cognitive. The question of territorial identity can be, and has been, researched from different prospectives by specialists of different professions – geographers, ethnographers, ecologists, architects, economists, sociologists, folklorists and others. In case of urban research, only a multidisciplinary approach allows one to cover such a complex organism or machine – whichever metaphor you use – as the city is, That’s why I use a package of methodologies – statistical analysis of data (applying to regional syndrome methodology), interviewing and running a survey, field monitoring, mapping and map analysis, semantic-statistical analysis of media and social media. As a basic unit of territorial differentiation I have taken a district (rayon)- the ultimate formal spatioadministrative element. The district’s division with local administration is the main principle of running governing processes in modern metropolises such as London, New York and others. And Moscow, as well, with this exception that heads of the councils are not elected, but appointed by the mayor, and have very limited decision authority, focused mostly around provision of urban amenities. The modern territorial structure of the capital of Russia has been established by the law 13-47 “About the territorial division of Moscow city” (5 july of 1995), which has been several times edited (in 2002, 2007, 2010) and was updated in 2012 according to the spatial extension of the Big Moscow project. It has taken into account previous research about Moscow districts, concerning different sides of the topic, that has been done before by Genplan Institute, socio-economical and electoral geographers, and the attempts to build the city index, made by A.Popov in 2008 in his dissertation and SLON.RU in 2010.

m acr o sc ale a n alysis Macroscale analysis was done by using the “Regional syndrome” methodology, that has been developed by two russian geographers (V. Kagansky and A. Novikov). It aims to characterize outlined territories. V. Kagansky and A. Novikov have applied it to USA-states and USA-counties. In this research I am building a Moscow district’s typology based on this methodology. The term “syndrome” by itself was taken from medicine and psychology. Its idea is that there is an association of characters that usually “come together”. If we meet one

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t

“PASSPORT” OF KUNTSEVO 29,7% residental area 8,6% industrial area 31,5% greenery 1,8% water 20,1 m2/capita 5153 $/m2 299 citizens/ha higly-educated people: 39% studing at middle-school: 6,5% 69,4 places in schools/1000citizens 17,1 hospital beds/1000citizens 1,8 chairs in hairsressing salons/1000citizens municipal budjet: 445rub/capita

of them in some situation (in the case of medicine it’s a decease, in case of geography and urbanism it’s a territory within some borders, a state or a district) we more or less credibly may apologize for the presence of the other characteristics from the group of “coming together”. According to Kagansky&Novikov it is not so important to look at all characteristics of any territory to define and understand it, but it’s much more important to look at these particular ones (so-called “regional cortege of characters”) that distinguish a state or a district from others ultimately. From one district to another the cortege differs, or floats, – that’s why we can talk about “a floating character” or “a floating cortege of characters”. All accounts were done within the spatialadministrative devision of Moscow before 1 july 2012 and will not include new territories of Big Moscow, as there is no available statistics about that part of the city’s territory yet. The model of the typology is built on 15 parameters, grouped into 5 clusters: 1) Land use distribution (% of residential area, % of industrial area, % of green zone, % of water, % of roads); 2) Demography (population density, % currently being educated in middle school, % of highly educated people) 3) Housing (average price $/m2, living m2/ capita) 4) Social infrustructure (places in schools/ per 1000 citizens, places in hospitals/per 1000 citizens, chairs in hairdressing salons/ per 1000 citizens) 5) Budjet (rub. of municipal budget/capita). The choice of data-sets for analysis and interpretation directly depends on the accessibility of statistics. Unfortunately, some important categories are missed, such as crime, ecology or architectural morphology, for obvious reasons – lack of data. Petrovka38.ru, for example, has not opened statistics about crime yet – concerning Moscow districts, but promised to do that in nearest future, and there is no a unified source of ecological information, although

68

some interesting projects exist (made by Faculty of Geography MSU or commercial companies). It is individually worse to mention that one of the results of this research is an extracted data about functional zoning. I worked with 2 sources (Genplan 2025 map and OpenStreetMap), inspecting the scrapped statistics in comparison to the Genplan Institute statistics of several selected districts (maps of them were kindly given for the author of the research by Genplan Institute for researching purposes). It turned out that OpenStreetMap gives more precise information with a minimal % of inaccuracy. The received statistics allow one to count density in a more appropriate way than it is usually given in open sources: density/residential area vs density/total area of a district. Data has been analyzed according to such a procedure: for every parameter the average value has been taken. After that, for all parameters, normalized dispersion has been taken and then the 3 the most remote from the average value characters have been selected. 3 is enough to demonstrate the model of the typology, but is not an obligatory number. It can be 5 or 7 characters, or even more, depending on the amount of parameters that have been analyzed. These are examples of “floating corteges”: Lomonosovsky – high % of residential area, low % of industrial, low % of water (0%). Kapotnya — high % of industrial area, low % of residental, low % of highly educated people. Kurkino – low % of density (counted in application to residential zone), high amount of living m2/capita, high amount of places in schools/1000 people. Yakimanka – high property prices, high amount places in hospitals/per 1000 citizens, high % of water area. The choice of the 3 most distinct points (both in positive and negative sense) give us an opportunity to read the urban character of each district, based only on numbers. These 3 characteristics are signals – they manifest big potential in using green territory in the


m a p p i n g

t h e

s t a t i s t i c s

8320-9415

46-55

7225-8320

38-46

6129-7225

29-38

5034-6129

21-29

3939-5034

12-21

N/A

N/A

Image 6. Property prices, average, $/m2 (IRN.RU)

210-255 164-210 119-164 74-119 29-74 N/A

Image 8. Places in schools/1000 people (Mosgorstat)

Image 7. Housing, m2 of living area/capita, in average (Mosgorstat)

7-8 5-7 3-5 2-3 0-2 N/A

Image 9. Places in hairdressing salons/1000 people (Mosgorstat)

472-584

15-18

360-472

12-15

247-360

9-12

135-247

6-9

23-135

3-6

N/A

N/A

Image 10. Density, people/ha of residental area (Mosgorstat, OpenStreetMap analysis, see Image 2)

Image 11. People, studing at the middle school, % (Census, RIA Novosti)

The central districts demonstrate their elite status: the highest property prices (Image 6), the lowest density (Image 10), good satiation of social infrustructure (Image 8,9). The more precise way of reading the maps - comparing district to dictrict.

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92,8%

district or a cluster of hospitals, which means a high social value of this territory within the city. For sure, the cortege by itself and each chosen characteristic needs a more precise look. In general the results are manifestations of the particularness of the distircts, proven by statistics.

51,7%

50,6%

50,2%

50,1%

23,5%

22,0%

17,2%

22,7% 18,2%

7,4%

m icr o sc ale a n alysis Macrodata ignores the microscale level of looking at the city, the subjective component of perceivig and living the city space (Jacobs) - that’s why I decided to organize a survey and collect opinions about districts from citizens. The survey had about 30 questions and was spread on the Internet through social networks and networks of professional organizations (such as the Institute of the Economy of the City, Big City magazine and activists networks such as Mosgorchat and Open Arbat). Also, the survey was partly done in paper form, aiming to cover the audience that is not represented through the Internet (old-aged people). From 9 may to 20 may 2013 about 600 people have participated in the survey. Here I’ll give an overview of the results only partially.

hate

hate very much

neutral

love

love very much

10+

food shop

3-1

hospital

1-3

child’s school

The “regional syndrome” methodology allows, as well, to single out the most archetypical Moscow districts - those ones that demonstate the closest position to the average set of parameters. For the combination of selected characteristics these are Kuntsevo, Losinoostrovsky, Alexeevsky, Timiryazevsky. For functional zoning’s set - Kuntsevo, Ramenki, Losinoostrovsky, South Tushino. So, we might choose two of them which are present in both groups – Kuntsevo and Losinoostrovsky – as the most typical ones for Moscow, the ‘most Moscow Moscow’.

4% 0,4%

0-1

job

The final results of the choice of a “floating cortege” of 3 for all districts are presented on a “psychodelic” map (Image 1).

Image 13. Survey results: a - mobility within the city: how long people live in their districts b - from home go by foot to..., c - do moscovites love their district?

One of the most interesting questions in this context is: “Which district will you choose if you will have an opportunity to choose any one?” It supposed a free thinking-imagining, and the answers show the popularity of different districts, and the “desirability” of them. Through analyzing the answers, we observed some tendencies: 1) peripheral people would like to move to the center of the city (Khamovniki and Basmanny are the learders), 2) the majority are dreaming to live near a park (Vorobievy Gori, Kolomenskoe, Tsaritsino, Lefortovo, Botanichesky sad, Serebryany Bor), 3) people demonstate the desire to move to one of the neibour-districts – familiar neibouring territories are attractive. It’s possible to single out several clusters of territories that sympathise with each other: the first one is Shchukino + Strogino + Krylatskoe + Kuntsevo, the second one – Severnoy Tushino + Yuzhnoye Tushino + Pokrovksoye-Streshnevo + Sokol, the third one – Arbat + Khamovniki + Yakimanka + Presnensky + Tverskoy. About 25.5 % of respondents prefer to live at their own district and about one third of them are very categorical in their desire and are not ready even to dream about changing the territory. The most devoted citizens live in Sokol and Arbat. By the way, one of the strongest motives for changing the district is nostalgia (have lived there in childhood, great grandfather has lived there and father has grown up, enjoy the atmosphere of the distirct), but not the commercial issues.

houses

dense

Image 12. What citizens LIKE and DO NOT LIKE in their districts according to the survey result. The “sygnal in the noise” here is a radically negative attitude towards the construction of north-west chord, which was announced by all respondents from Koptevo: they believe this road will “kill” their district. Should the authorities take into account opinions of citizens while solving transport problems of the city?

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Image 14. The most desired districts to live in, according to the survey: Khamovniky, Basmanny, Zamoskvorechie, Presnensky, Tagansky, Sokol, Gagarinky, Ramenki, Izmailovo, Aeroport, etc

inv isible dis tr ic t s The survey’s responses has sorted out the whole group into, lets call them so, pseudodistricts, that are not official ones, but are recognized by citizens as districts: Patriarshie prudy, Chistie prudy, Kitaigorod, Ivanovskaya gorka, Frunzenskaya naberejnaya, Dinamo, etc… This phenomenon is not something unexpected. While the

m o s c o w Name of a vernacular dictrict

government propose and outline official borders of territories, which are formal, important in administration and budget assessment processes, citizens unconsciously, instinctively and spontaneously single out their own districts, which are not formal but socially very powerful – these are vernacular districts. It’s people’s response to official division and the evidence of people’s perception of the city space. It’s the spatial expression of the territorial identity of citizens and the marks of the borders of one or another city’s community. Citizens feel something very specific towards these kind of territories – local patriotism – and are ready to unite, to mobilize in case of emergency first of all within these types of districts (Puzanov K.). In the USA some cities (San Francisco, for example) demonstrate a very strong vernacular division of the territory, while Moscow is much more spatially chaotic. In this report I am figuring out only some cases (see the table), that show different types of vernaculars being present in Moscow. I’ll describe one of them – Arbat – in more detail. Arbat is an official district within the central administrative okrug. At the same time it is the name of the street which is one of the symbols of Moscow. And at the same time it is the name of a vernacular district which has the same name as the administrative one, but not the same borders. If we focus on the answers to one of the questions of the survey (“What are the borders of your district in your particular perception?”) we will see an iterative “mistake” in defining the borders. Even two: one official border is almost always moving from Povarskaya street to Novy Arbat and another, from time to time in the answers, is moving from Sivcev Vrajek to Prechistenka street or even

v e r n a c u l a r :

s t u d y - c a s e s

Description, type of borders

Location

Principle of formation

Arbat

The name duplicates the names of the official district and the name of an old pedestrian street. The borders are movable, penetrable.

Between Novy Arbat, Ostojenka, Gogolevsky bulvar, Sadovoe koltso. Partly overlays an official district Arbat, partly moves to Khamovniky district territory.

Highhways (Novy Arbat, Sadovoe koltso, Ostojenka) extrude the smaller streets, which are the borders of a formal district (red on a map), and shape the vernacular (yellow).

Kitai-Gorod

Was singled out around the historically valuable area with the same name (red on a map). The borders are movable, penetrable

Around Kitai-gorod metro-station. Includes the next streets: Iliinka, Varvarka, Maroseika, some people even include Pokrovka.

Adaptation of a historical toponym.

Map

Block of Red Houses

Vernacular combines 2 blocks of houses (7 buildings for each block). The borders are immovable, penetrable.

Stroiteley street 4, 6. Within Lomonosovsky official district.

Socio-architectural principle of formation. The block is an architectural experiment from 1950e: the facade is decorated with red tiles (A.Melii tiles). Majotiry of inhabitants - professors of MSU and their offsprings.

“Grey City”

An informal settlement of migrants, which already exists for several years. The borders are immovable, impenetrable.

Close to the metro-station Universitet. Within Lomonosovsky official district.

Ethnical settlement of migrants.

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Image 15. “Special days” on Twitter: Victory Day, 9 may 2013, and Meeting-on-Bolotnaya Day, 6 may 2013. Analysis of social media (for examples, geo-located twitts) make it possible to observe patterns of mobility of citizens and their involvement in public events. On 9 may there were registered intensive crowds on Tverskaya street and Kuznetsky street, Arbat and Novy Arbat - these streets were the most occupied by public holiday programme. On “usual” weekends twitt analysis does not show this kind of crowdedness on the same streets. Map of 6 may shows the meeting footsteps: the Bolotnaya Square was more heavily attanded than on “usual” days.

Ostojenka. So we may conclude that it is not a “mistake”, but a manifestation of existence of vernacular district. It’s apperance has roots in historical transformations of this area and cannot be “recovered” by an official territorial devision by a wave of a magic wand.

c o n clu sio n s As a conclusion I might estimate several statements. Official and commercial statistics might be considered as a basement for defining territorial differentiations - even being not 100% reliable this data allows one to identify urban characters of Moscow districts and specify their peculiaritires. Intendment of the territorial differentiation within official borders is not enough if we want to understand Moscow. Vernacular districts manifistate the bottom-up processes of “appropriation” of the city space. Information about vernacular districts and inner borders in the city (it might be imagined like a new layer on OpenStreetMap, for example) show heterogeneity within official districts. Creation of an information system (city index) is a necessity nowdays - interests of stakeholders and citizens are on hand.

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p r o p o s al My proposal is: participatory city index. Traditional indexing systems (for example, the index done by SLON.RU in 2010) operate with “objective” data and do not take into account citizens’ opinions. I propose to build a modified model of the index that will include participation of people who live in the city and have a personal idea about the city space and their districts. Collecting “perceptions” (through the appraisal plan towards official numbers) will help to build a vivid, dynamic information system that doesn’t only “spit out” the information, but also has a space for reaction on official statistics, and space for transformations according to gathered reactions. Personal citizens’ opinions are subjective, but when there is a mass of such subjective opinions they have the power to highlight some patterns or tendencies. The index model needs a more detailed development. Here I am announcing the basic principles of the participatory index: dynamic structure and sensitiveness to voices of citizens. In a schematic way it looks like this: data → reaction → citizens’ sensitive data.


District Profile Arbat

Average Income per Capita, $, Russian Research Group

r e fer e n c e s Distance to Kremlin, km, Google Maps Population, Mosgorstat

Highly-Educated People (%), Census, Rosstat, RIA Novosti

Total residental area, m2, Mosgorstat

Property prices, $/m2, IRN.RU

Gold J.R. An Introduction to Behavioral Geography. Oxford, 1980. Hague C., Jenkins P. Place Identity, Participation and Planning. - Routledge, 2004. Jacobs J. The Death and Life of Big American Cities. Hardcover, 2013. Jones A. Human Geography: the Basics. - Routledge, 2012. Lefebvre H. The Production of Space. - Oxford, 1992. Neal Z.P. The Connected City: How Networks are Shaping the Modern Metropolis. - Routledge, 2013. Shortell T., Krase J. Place, Space, Identity: A Spatial Semiotics of the Urban Vernacular in Global Cities, 2010. Soja E.W. Postmodern Geographies: The Reassertion of Space in Critical Social Theory. - Verso, 2011. Tuan Yi-Fu Space and Place: The Perspective of Experience. - Unoversity of Minnesoya Press, 2001. Baevsky O. Modern Town Planning Practice and Masterplan of Moscow.

Kagansky V., Novikov A. New Method of Separation Characters for Designing Regional Classifications.

Profiles Comparison N e w H orizo ns of Big D at a p olit.r u, 1.03.2013 Popov A. Valuation of the Territorial Differentiation of the Quality of Moscow City Space. Dissertation.

The Potencial of Big Data Pro et contra # 6 (57) 2012. Puzanov K. Intracity Selforganization of the Society by Example of USA, Russia and Countries of European Unity. Dissertation.

Arbat - Zamoskvorechye (Center- Center)

Arbat - Krylatskoe (Center- Periphery) Smirnyagin L. About Regional Identity.

Vendina O. Social Atlas of Moscow.

http://slon.ru/moscow www.data.mos.ru gpinfo.mka.mos.ru www.mosstat.ru w w w.openstreetmap.ru http://w w w.city-data.com/ http://citydashboard.org/london/

Krylatskoe - Golyanovo (Periphery-Periphery)

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T HIS IS S M A R T-A! A n e ssay o n h o w s m a r t is t o o s m a r t Katerina Examiliotou & Glafira Parinos

Will DATA save Moscow?

Will

Moscow

be

smarter/better/

stronger/faster if it uses smartly its data and technologies?

Do we really want Moscow to be smart?

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Image 1. E.Savelev, Noon 2017 glitched

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“Over the coming decades Russia should become a country. Prosperity is ensured not so much raw material as intellectual resources, “smart” economy, creating unique knowledge, exporting new technologies and product innovation.” Dmitry Medvedev Premier Minister of Russian Federation 29/05/2013

in tr o d u c tio n Doing research about data and the city was based by the studio on the premise of the accelerating amount of information being created every day about the urban environment, leaving traces in it. With the hope being to reveal new ways of understanding the city, new tools and new decision making processes, we dug into the data, the new technologies and their application in city planning. Using data is not a new idea, every kind of planning throughout the history is based on information. The difference now is the amount that is already available in real time. With respect to urban data in Moscow and for how it matters today, we thought of its application, where it’s actually being used. That led us to the trend towards “smart cities”, as their popularity has emerged in parallel with the surge of big data and increased use of sensors. “Smart cities”, more than a theoretical model, seems to be inevitable, as its concepts are already being implemented in numerous cities around the globe. Since the global trend toward cities getting smarter is growing, Russia in general, and Moscow in particular, have made an effort to catch up. The State seems on the edge of enhancing a digital state of being, Skolkovo is being designed and advertised as a smart model, the discussion about the city’s open data is hot and ongoing. But can Moscow actually follow up to the trend? And perhaps even more importantly, should it? With that in mind, we identified the necessity of researching the concept that already exists and seems about to be implemented looking at the whole picture rather than the specifics. This paper intends to examine whether Moscow should engage to those smart policies or if it is a premature interpretation of fast track “solutionism”, based on wrong or manipulative assumptions. If so, under which conditions could Moscow become smart and what city would that lead to?

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a n alysis Why smart cities? Looking into papers and articles regarding smart cities, the majority are being justified by the increasing urbanization. As cities all over the world started accumulating more and more people every year, the existing big urban problems of traffic, education, energy management, public safety, are seeking for new solutions. Parallel to this, developed countries have stepped into the age of information and technology, huge corporations sell more and more technical equipment to the cities and the penetration of Internet has grown in the last 12 years by 566%, reaching 35% globally in 2012 (Miniwatts Marketing Group, 2012), with the figures for the developed world being much higher. These factors forced to enhance the previously stated problem solutions with existing technologies. Moreover, the technological presence grows in the urban environment with smart personal devices, intelligent transportation systems and smart self driving cars etc. It seems that the existing model of the city is no longer good enough, as proposed solutions to these problems come more and more from technology companies but not urban planners. IBM, Siemens, Cisco are ready to identify the problems and offer solutions on a respected price, claiming a key position in the urban planning market by introducing sensor technologies, real time data processing tools and prediction softwares. The data is here to save our cities, as with its help and with stated companies’ management they will evolve into something other than their current reality. “Now, they have information to say why problems occur, where they are and what can be done to prevent them. At the end of the day, it is all about managing information to improve operations.” Guruduth Banavar, chief technology officer of global public sector efforts at IBM (Chapman, 2010).


Michelle Proovost, director of International New Town Institute, during our talk at Strelka (23/04/2013) suggested that “Urban Planning is not what urban planners do. There are a lot of parties being involved, private, governmental and these parties have different responsibilities. The problem exist when the control is concentrated in one man, in one party. You cannot expect from private parties to have the same ideas as the public. Their goal in life is profit; not public interest”. Companies appear to offer the urban intelligence that our old-school planning or designing have been unable to complete. City leaders entrust the city’s intelligence on innovation, global competitiveness and investments in infrastructure. (What Makes a City Smart?, 2012) So here comes the concept of smart city!

Smart mobility (Transport and ICT, accessibility)

Smart economy (Competitiveness, productivity)

Smart environment (Natural resources, environment protection)

Smart living (Quality of life, culture, healthcare, etc)

What is smart city? A city performing well in a forwardlooking way in economy, people, governance, m obility, environment, and living, built on the smart combination of endow ments and activities of selfdecisive, independent and aware citizens. (Centre of Regional Science (SRF), Vienna University of Technology, 2007 As the concept is still emerging, there is not a concrete definition in use. One could say that smart city is a complex concept that includes management of different spheres of city life through new emerging technologies. They use measuring sensors, surveillance systems, even prediction simulating software to make the city work better (Ruvolo, 2011). There is not any general m odel of implementation as every corporation develops its own scheme. The key elements that the city should carry as infrastructure in order to become smart vary from smart grids to transport infrastructure and from waste management plans to platforms that allow citizenstate corporation. Expect the already stated requirements, it is essential for the smart m odel to be built upon unconditional openness of information, transparency within the government and the decision making process, as well as civic engagement. “Smart Cities need true openness of data. It is not simply a case of governments opening up their data to everyone on public platforms. It is individual citizens and privately-owned companies offering their data to the government or government departments sharing their data with one another. “ Open Science Series, 2013

Smart governance (Participation and transparency)

Smart people (Social and Human Capital, Social and ethnic plurality)

To be able to accom modate the expected new inhabitants, contemporary cities have to be smart and hyper efficient! Where does the obsession of efficiency come from? How did it become the new paradigm and why? Is the amount of information that can be collected and analyzed in real time a valid argument for eliminating any possible errors?

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“Solutionism: an intellectual pathology that recognizes problems as problems, based on just one criterion: whether they are ‘solvable’ with a nice and clean technological solution at our disposal.” (Morozov, 2013)

"We want an architecture adapted to our world of machines,radios and fast motor cars” Walter Gropius,1923

“city as an efficient, fast-paced machine” Sant'Elia

MODERNIST CITY

INDUSTRIAL CITY

Une cité industrielle Tony Garnier,1917

Città Nuova Sant'Elia 1904

SUSTAINABLE Sustainable Poster, 70s

“an intelligent building can include the technology to allow for devices and systems to be controlled automatically.” Atkin, 1988

Electronic Urbanism Takis Zenetos 1969

Plug in City Peter Cook(Archigram) 1964

"The Goliath of totalitarianism will be brought down by the David of the microchip" Ronald Reagan,1989

GREEN CITY

Neuromancer William Gibson 1984

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DIGITAL CITY

Building Cities for a Healthy Future Richard Register 1987

DDS (Virtual Amsterdam) 1994


"Sunshine, trees, hills and valleys, flowers and flowing streams. This world of tomorrow is a world of beauty. " Magic Highways,video 1940

From Industrial to Smart The new paradigm discourses: how can the ideal, the Utopian, be available as a ready-made product? ‘In large, these utopias stand for a city “brand” shaped under the influence of avant-garde technology. It is, in reality, a way to “advertise” the city and attract the kinds of dwellers and visitors that will lead to a prosperous economy, a practice known as “city branding” or “place branding.” (Angelidou, Tarani, 2012)

Magic Highways General Motors 1940

Popular Science Monthly 1925

Life Double issue on Cities 1965

SMART CITY

In a modern city, a robust digital infrastructure is essential to manage the physical resources and ensure that the city will be liveable and sustainable over the long term. Guru Banavar - IBM

IBM 2013

Anthony Townsend, Director of Technology at the Institute for the Future (Palo Alto, California), argues that IT companies are rushing into becoming a factor, without which the cities could not function. In that respect, he identifies similarities with the vision of utopia that was “sold” by General Motors in 1940 within their advertising campaign, and lead to urban sprawls and very high-energy living. Now, likewise then, the vision is being created and sold from those who manufacture the product around the product itself. (New Technology Smart Cities, 2011) In addition to that, if smart cities are considered to be data byproducts, Kazys Varnelis, Director of the Network Architecture Lab at the Columbia University Graduate School of Architecture, Planning, and Preservation, suggests that datascapes, and therefore these cities, are not natural.

The Walking City Ron Herron(Archigram) 1964

Masdar Norman Foster 2008

“It’s alm ost as if things can be boiled down to a simple equation: technology plus innovation equals urban sustainability,” (Humphries, 2013)

“What I am suggesting is that the data we choose, generally speaking, is constructed by humans and how it’s constructed is crucial. It’s often presented as ‘this is it’, the future of the city will be this based on these projections, but what are the assumptions? Why? Who benefits? Its alm ost like a new religion. When you believe, you give your self up to that thing, you give up your data and it’s like you’re giving yourself up, you belief in this thing, you believe in the power.”

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Implementation As the cities are getting “smarter” around the world, there is analysis of international experience of the adaptation of the smart city concept. There seems to be two ways of implementation: t

In a newly built city, “new towns”, in Michelle Provoost terminology, like Songdo. Uniting existing technological initiatives within “old” cities, like San Francisco.

t

The first scenario is applied mainly in developing countries, while the second scenario can be found in developed ones. The first scenario is applied mainly in developing countries, while the second scenario can be found in developed ones. The popularity of the concept doesn’t come without reasons. A city being smart is a city that use technology to its benefit in order to make every possible procedure faster and simpler for the citizen. It is able to plan its resources according to its needs, to m ove people around in the fastest and m ost customized way and it shares all information with the people in order to allow the participation and development to come from the bottom up as well. The benefits are quite tempting and speak of a future that naturally every city would like to take part in, as it is the need of true sustainable living that lies beneath it, as the needed evolution of our current state. Both ways of implementation deal with the city, for the m ost part, on an intangible level. In a way, what is being perceived as smart, regarding the building environment, is just a small part of the full package. The building structure doesn’t change dramatically (buildings, roads, open spaces), but new “invisible” layers of the city are being added. There is no such city in the world yet that has implemented efficient technologies in all spheres of life. What are the changes that happen to a city after it has been proclaimed to Projects be smart? Smart City by Primary Industry Sector, World Markets 1Q2013

“We’re trying to replicate cities, but we have no standards.” Wim Elfrink, Executive Vice President of Cisco Services

Governance Integrated security command center (Lavasa) Automated messaging from a citizen call center (Lavasa) Consolidated billing (Lavasa) Managing system / reduce of bureaucrats

Economy Business corners for small businesses (Cape town) Digital business centers with equipment, (Cape town) Business incubation center (Suwon) Climate street (Amsterdam) Electronic trade office (Suwon) Heavy industries at outskirts Tax incentives

Environment / Energy Low carbon footprint (Toronto) Smart Girds (Dublin, Malaga, Masdar)) Smart Meters (Amsterdam, Chattanooga) Renewable energy sources (Malaga) Electric vehicles (Amsterdam, Malaga) Power quality monitoring (Lavasa) Energy conservation monitoring (Shenyang)

Living Online available public utilities Water and sewage (Gdansk, Shenyang) Waste management (Planit Valley) Food supply (Shenyang) Urban-monitoring system (Rio de Janeiro) Home automation (Lavasa, Malaga and Masdar)

People Broadband development (Chattanooga, Dakota) Internet access in public libraries(Cape town) ICT sector support and ict training(Cape town) Jobs in hi-tech sphere. Middle and upper class (Songdo)

60 50

Mobility

40

Number of 30 tracked projects 20 10

Smart Energy (incuding water)

Smart Goverment

Smart Mobility

Smart Livings (Buildings)

Nikkei BP Clean Tech Institute 2012

Smart City Projects By Primary Sector, World Markets IQ2013

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Public transport, one card system (London) United net of moving goods vehicles (IBM) Combined transport terminals(IBM) LED/smart traffic lights Smart intersections (Singapore, Smarara) Customized routes/CCTV of traffiс (Rio) Зarking management technology (Lavasa)


#2 USA

#7 Former Soviet Union & Eastern Europe

#3 EUROPE

US$ 6.7

US$ 6.85

#1 CHINA

US$ 1.36 US$ 7.45

US$ 1,17

US$ 2,58 US$ 1,28

US$ 4,27

US$ 1,45 US$ 0,69

Estimates on world Smart City Market Nikkei BP Clean Tech Institute 2012

World market of smart cities For such projects to be implemented Harvard Business school notes that the capital cost(estimated between 10 bln US$ for PlanIt Valley and 35 bln US$ for Songdo) typically requires funding from both the public and private sectors. For some projects, such as Masdar, Nanjing, Meixi Lake and Tianjin, governments provide a significant portion of the funding through state-owned banks or direct public sector financing. However, in some cases, it is expected that private developers and third parties will provide most development capital after the initial development phase is completed. Globally, there are around 700 cities, each with populations exceeding 500,000 and are growing faster than the average growth rate of cities. This opens up the market for industry players to grow their business in new and emerging smart cities. The infrastructure investment for these cities is forecasted to be $30 trillion to $40 trillion, cumulatively, over the next 20 years (Nikkei Business Publications, 2010) With the estimated market being too big to demonstrate a trend to be taken seriously, it seems that there is a lack of efficiency assessments. The majority are done by the providers of smart city services, which makes them biased. There are just a few supposedly independent ratings. According to Boyd Cohen’s (Ph.D. Urban & Climate Strategist, Professor, Universidad del Desarrollo) survey, 10 cities from his list of the best smart

cities in the world will spend roughly $40 billion on smart technologies by 2016 (Johanson, 2012). Commision on Smart Cities and Communities of the European Union will become a part of a large scale tactical program, Horizon 2020 (The EU Framework Programme for Research and Innovation, 2012). The Commission has substantially increased funding from €81 000 000 in 2012 to €365 000 000 in 2013 (Smart Cities and Communities Communication, 2012) According to Cohen (2012), the smartest city in the world is, surprisingly, Vienna. But the number of ratings in this field of knowledge is numerous. Another list puts San Francisco on top (Delgado, 2013) or Singapore (Kotkin, Laneri, 2009). Although, the criterias and indicators of city performance assessment do likely lie in the same field (grid employment sector, decrease carbon footprint, smart transportation, waste management, city applications, business development), there is no unified system of estimation. The definition of “smart city” is also variable. More or less, this system is established in the European Union, who publish annual reports on midsized smart cities. Except from this, there are almost no alternative assessment reports on city performance after the introduction of this system. The lack of proper assessment creates a default situation where the city’s smartness is evaluated by those who are directly involved in the smartification process. Therefore any critic can not happen based on objective factors.

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Image 3. IBM Smart Planet

Image 2. Global Energy System, 06/1969

Image 4. Siemens Smart Grid

the context: Russia_Yesterday We consider the big “smart city” idea as the outcome of a wider historical context of “solutionism” and therefore we can identify a correlation to the recent past. Big ideas that promise to improve our living conditions are certainly not new to Russia. The idea of making cities efficient and smart can be traced back to the USSR. Planned economy was aimed to drag Russia onto new industrial rails and this process was accompanied by massive visual propaganda – posters, theatrical performance. Newly built cities in the Soviet Union, that were built according to communist utopian ideas, such as Dubna, Tolyatti and Magnitogorsk, and also monocities, were supposed to provide systainable living for a while. Breaking down the promoted vision to its elements, from one hand, there was the straightforward propaganda where the data appeared to be clearly manufactured and, on the other hand, the future image of the Soviet cities was presented in the most phantasmagorical way. The exaggeration of these possibilities is quite an interesting case. It consists, along with the use of appealing imagery of the country’s well being, as a distortion of reality, a pure visual rhetoric aimed to persuade with no evidence. In that sense, one could

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argue, that the language of propaganda resembles the language of these new “smart utopias”. They are represented as well by the use of imaginary urban environments which might not look as ‘fairytail-y’, as the soviet ones, but using a contemporary visual vocabulary: white renders, colourful representation of the additional invisible layers, comic aesthetics and bold statements, attempt to foresee the future. It seems, as to sell the utopia you always have to use the same language.

the context: Moscow_Today “The Capital of Russian Federation is to go through a substantial transformation never seen before by any global city, to grow as smart, intelligent and ecological. The Smart Moscow Strategy aims to model Future Moscow as the largest Eco-intelligent urban ecosystems in the world. “ (Azamat Abdoullaev, PhD, Managing Director) “Russia is in top-5 countries, along with China, USA and India, that should expect a boom of technology in the nearest future.” (Mark Minevich, president of Going Global Ventures, co-director of BTM Institute, USA)


Moscow, with a 52 400 000 US$ budget, holds the third place in the world rating after New York and Shanghai and the trend is planned to keep growing every year (Key indicators of the cities of the world, 2013). It is evident from the spending that the direction of policy chosen by Moscow Government is very “social” with the main expenditures on healthcare, education and social safety net (Budget expenditures in Moscow, 2013) Within that framework, the direction of “Innovative Development” appears to have several parts and one of them includes spending on the state program, “Informational City”. This program intends to raise the quality of life in the city with help of information-communication technologies. But, despite the intention that the spending demonstrates, could we argue for the existence of features that will see the implementation of the ‘smart city’ concept in Moscow?

Manipulation “Information and communications - particularly ubiquitous broadband Internet access - are vital elements in any definition of the ‘smart city’. But a city only becomes smart if it can make use of these capabilities to deliver real-time services based on the capture of information.” Eric Woods, Pike Senior Analyst, co-author of the Smart Cities Report by Navigant (2013) With the question regarding the information being raised, one of the first possible issues is the manipulation of that very information. Manipulation of data doesn’t, perhaps, sound like groundbreaking news:

“So much data manipulation is going on around us!”

Sergey Chernov (Ph.D., Data Deputy Director of the Center for Internet and Society), 19/03/13 "Informational City" Investment million roubles

250 waste water emission 200

150

100

50

0 2000

2001 2002 2003 2004 2005 2006 2007 2008 2009

Built Structures and Waste Water Emission http://www.gks.ru/

Census

-17%

7% 17% 30% 43%

100% 11,5 mln

http://www.gks.ru/

Mortality

9,5 mln

http://polit.ru/

FMS estimation

12,3 mln

http://www.fmsmoscow.ru/

Zubarevich N.

13,5 mln

http://www.opendemocracy.net/

Sim Cards

15 mln

http://www.acm-consulting.com/

Dzhurayeva G.

16,5 mln

http://www.telegraph.co.uk/

Paleev A.

22,3

http://www.rosbalt.ru/

“They have 2 sets of data, one for leadership and one they publish IF they publish” Murray Feshbach (Ph.D., Chief of the USSR Population, Employment and Research and Development Branch in Center for International Research of the Census Bureau), 13/03/13,

2010 2011

Moscows Population Estimations

but it becomes worth considering that the ‘smart city’ is being built upon these datasets while creating new ones. So, further decisions are made on wrong assumptions. Through the studio’s research, we stumbled upon issues of reliability, accuracy and manipulation of data and through data. For example, the waste water emission and the build structure, two completely different indicators, appear to have the same curve of growth from 2000 to now (2013). While this evidence reveals the unreliability of data, it also hints at the possible manipulation of it. Regarding that, measuring population of the city can also be considered as

image 5. Investment in

image6. Production of

National Economy in USSR

Electricity in USSR

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an example. Perhaps the distorted outcome is not as extreme as it was in USSR where in ‘39 a report was issued of just 10 pages for the whole country’s population (Tolts,1995), but still experts seem to have good enough reasons to discard the truthfulness of the numbers published from the latest Census. The data inconsistency within the state could mean that, despite the availability, the databases shouldn’t be used as such in order to provide the foundation for the new smart, improved governance system. The new smart infrastructure aims to respond to the cities true needs. Considering transportation, hence traffic, which is one of the key problems in Moscow, would the smart solutions be the same whether there are 11 or 15 million people in the city?

Transparency Moving on, one of the key principles of the contemporary efficient ‘smart city’ is transparent governance. Since September 2004, according to amendments to Federal Law 184, direct elections were abolished. Since then, mayors of Moscow and St.Petersburg were appointed. Political scientists, sociologists and mathematicians analyzed the results of elections on 11/10/2009 to Moscow Duma, where the first place by far had been occupied by United Russia, a party in power, as observers reported abuse and violation of the electing process. By applying well-known statistical methods from probability theory to open data that represented the results of elections, they were able to demonstrate that the results were manipulated and there should have been 3 more parties in present Duma. “In Moscow no one was waiting for flourishing democracy, but it was able to beat the most pessimistic forecasts”, (Alexander Kynev, PhD in Political Science, head of Regional Programmes at Development of Informational Policy Foundation.) The fact that the fraud was detected by both observers, but also, and more importantly, statistical assessment by different people - professional experts and simple citizens, mainly bloggers - brings us to another important aspect of smart governance - the civic engagement in decision making and the controlling process. The election example demonstrates the people’s will to engage, while showcasing clearly that the State is not fully committed towards that direction, but approach it in an epidemic level of developing applications for submitting the reports on public works and service needs.

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Technology provides possibility to broaden the process of engagement, that’s why the number of mobile applications are often used as an indicator in this field. The importance of city-managers being able to listen to citizens and providing possibility for giving feedback is undeniable, but should go beyond that.

Corruption The implementation of a ‘smart city’ concept is strongly related to the financial state of the city. It requires a big investment to begin with, while it will supposedly provide an expected financial growth. But in the Russian reality it seems impossible to talk about big money without talking about corruption. “That’s where you’ve got to make the relationships and make sure it’s going right,” - Daniel Thorniley, president of DT Global Business Consulting about making business in Russia. (Dobby, 2011) Konstantin Sonin, a professor at the New Moscow Economic School, argues: “Once you’re in Russia, your margins are high — corruption, to some extent, once you’re in, it protects you from competition” (Dobby, 2011). The risks of doing business in Russia are, in one part, with those in Nigeria and Romania and can negatively affect sales, Coca-Cola said in a report issued to its investors. Coca-Cola’s main competitor, Pepsi, has also highlighted business risks in Russia. After last year’s presidential election, the company warned investors that political instability and civil strife possibly could have a negative impact on financial results (The Moscow Times, 28 February 2013) Transparency International ranks Russia 133 out of 182 countries in its Corruption Perceptions Index (Corruption perceptions index 2012, 2013) Corruption costs Russia about $300 000 000 000 a year, a full 16 percent of its GDP. And that measure doesn’t capture the distorted incentives and lost investment that are side effects. Russia placed last in Transparency International’s most recent Bribe Payers Index, which ranks countries according to their companies’ propensity to offer bribes (Bloomberg View, 9 May 2013). The Indem Foundation, a think tank that prepared a report last year for the Ministry of Economic Development, found that bribes are most often paid to the traffic police (about $800 000 000 a year) and by parents applying for child care or kindergarten spots. But the greatest volume goes to the health-care system — about $1 200 000 000 a year in small payments (Corruption and Human Rights in Contemporary Russia, 2012). Back to the ‘smart


city’ concept – these are some of the basic elements that are promised to be changed with the help of technologies.

Open data As stated previously, openness of information is one of the key elements of a city that claims to be smart. By the European Union definition, open data is general information that can be freely used, re-used and redistributed by anyone - either free or at marginal cost. The open data movement begins with publishing government reports by activists and random departments. This is already hugely valuable in developing transparency between government and citizens, something that is greatly lacking today in most cities. Opening raw governmental data became a strong trend, and since 2012 includes Russia and Moscow in particular. Dmitry Medvedev, after his election, introduced sort of digital-friendly and so-called ‘open’ governmental policy. All Moscow departments and courts were obliged to open their data to the general public. The Department of Informational Technologies appeared in 2010 but there is no unified format of the releasing of data till today. In 2013 all departments acquired user-friendly websites and the IT department launched web-GIS of Moscow. Prior to that only private commercial and noncommercial initiatives existed. So, introducing smart bus stops in a situation when not all of the ordinary ones are known doesn’t look like a profound decision. We don’t mind knowing when the bus is coming but the bus should come to the right place by the right route. We are not describing futuristic processes that might happen in Moscow. The smartisation of Moscow has already started, approaching closer and closer to Moscow. Since 20 May, 2013 Russian government has withdrawn its application from Open Government Partnership (Open Government Partnership, 20 May, 2013), an alliance of governments of countries initiated by Brazil, USA, UK, Norway, Indonesia, Mexico, Philippines and South Africa to establish common rules and standards of implementing open policy. What forced Russia’s government to withdraw the application? “OGP is a complex international project and Russia approaches it seriously. We do not need participation for the sake of appearance. … It’s important for Russian government that assessment of openness will influence credit ratings of the investment climate of our country, for example. In doing business of

the World Bank the participation in OGP becomes more pragmatic and effective for participants … Realisation of the mechanisms of open government will continue to be worked on and intensify … till 2018.” (Mikhail Abyzov, Minister of Open Government affairs, 21 May, 2013) Russia’s long-term ratings were affirmed by Moody’s at Baa1, the third-lowest investment grade, with a stable outlook, according to a statement dated March 27. Moody’s hasn’t changed the country’s rating since a one-step upgrade in July 2008, the last time a rating company improved Russia’s ranking (Rose, 2013) Moody’s and Standard and Poor’s credit reports on Moscow are pretty similar (Credit Ratings of Moscow, 2012). International rating of Moscow is the same as Russia’s one - Baa1 (Moody’s) or BBB (S&P). Agencies predict a deficiency of city budget because of variability of tax revenue. An important part (about 2%) (RBC, 21 May 2012) of tax return comes from oil and gas companies, whose headquarters are situated in Moscow. President Vladimir Putin approved a plan of registering big corporations outside Moscow (Lenta.ru, 26 April 2013). It means that companies will pay taxes where their production slots are. It will cause runoff of the money from Russia’s capital. Along with this process more money will be spent in communal service and transportation because of new Moscow territories (160 000 ha) that claim lots of investment because of underdevelopment. Decisions of deficiency of the capital’s budget is more determined by political will than a predictable economical process. Lacking money in city budget is the reason to attract investors. ‘Smart city’ is one of the features that can attract foreign investors. Proclaimed by companies that operating smart cities and efficiently working systems (water supply, energy and transport and human capital) are the keys to successful business. ‘Smart city’ offers transparency in relations with government that also attracts businessmen. It looks like there are two Russias - one is launching open government, publishing machine-readable governmental data, commending foreign experience in open initiativ – and that lies more in a field of PR. The second one argues that political powers in Russia do not need transparency as they do not understand the need for it. The uploaded datasets on the data.mos.ru platform are provided to IT department by the other ones. It’s only logical that the departments provide the information they use themselves in their work, because otherwise that would create unequal circumstances for government and private developers.

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In the beginning of 2013 on Tverskaya street the first “smart” bus stops were installed. They are fitted with antivandal touch-screens that show approximately (as explained, it’s for the period of beta-testing) the time of arrival of all the buses, bus routes and have a map of the neighborhood. According to the plan, framed by the state program “Informational City” of the Department of Transportation, 8 more smart bus stops will appear on the Garden Ring. Afterwards, all the bus stops in Central District (Okrug) will become smart while the ones on the outskirts and in residential areas will only have a news-ticker that shows the schedule. While the new ones are being implemented, it is worth taking a look at the dataset of the existing ones (Open Data Portal, 2013), as, by checking bus stops randomly, it is evident that there are a lot of mistakes. So, introducing smart bus stops in a situation when not all of the ordinary ones are known doesn’t look like a decision aiming to improve a situation, but looks like a plan to advertise the city. There is nothing problematic with knowing when the bus is coming but the bus should come to the right place by the right route… This is not the possible future Moscow: the smartisation of Moscow has already started and keeps coming closer.

Skolkovo The smartification of Moscow is more than the official intention. It has already started, with the first example being Skolkovo. Initially found as a business school, a shift to urban formation started on a “smart” basis, with different environmentally friendly transport, use of geothermal energy, solar panels and waste management. Initiated by former president Dmitry Medvedev and supported by Vladimir Putin, by Federal Law N 244 that was passed on 28 September, 2010. By now (May 2013) only one administrative building has been constructed, although it was announced that the technopark of 20 000 sq m would be finished by the end of 2013. A series of financial scandals are taking place that led to the initiation of a criminal investigation. Skolkovo’s patron, Vladislav Surkov, was suspended from the position of Vice-Chairman of Government of Russia along with several Skolkovo top-managers. When one of the top-managers of Intel came to Moscow to negotiate a 1 000 000 000 USD contract, he was taken in by an Investigation Committee for a few hours, deprived of documents and cellphone (Kanygin, 2013). After he had been released, he immediately left the

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Mistakes in old bus stops New Smart bus stops

Moscow Bus Stops in Open Data

country. Skolkovo made its apologies to Intel but the contract was tied up. The scandals of Skolkovo are not irrelevant in the ‘smart city’ talk. They demonstrate how innovation development is being highly promoted by the state and how strong conflicts of political interest manifest. Political will in Russia extremely strongly depends on personal relations of top managers Government can not be perceived as a single structure as business and power are accreted.

c o n clu sio n s I.OPENNESS For Smart Moscow to operate in an efficient manner it is necessary for the data to be truly open (as in every equivalent model). Given the situation with Moscow data, that’s not the case, so, for the system to operate, a need for change of data policy is essential. II.PEOPLE Behind the system are still people who it’s hard to change just by implementing smart informational coordination. That’s one of the reasons that digitalisation of the city and its shift from the post-industrial to the informational era should evolve incrementally.


III.PROPAGANDA The smart concept is being used as a new form of global propaganda. It requires huge investments for it to be implemented while focusing on random aspects (like bus stops) that work as a marketing strategy / branding opporunity for the city, rather than addressing true solutions. IV.BUILDING ENVIRONMENT The changes that will come out of that model are happening for the most part to an intangible level rather than the building environment. Despite the fact that the buildings stay the same, there is the danger of a shift in human topography as the smart changes are approachable and affordable for a certain group of people, excluding the rest. This utopia is not for all of us. That could lead to a new social zoning with parts of the city being highly digitized and the rest falling into a decay or disappearing from the map or the emergence of sellers of ‘smart city’ addresses to city-managers and big businesses. This scheme mainly excludes civil activists and citizens. Initially, the talk is about money but not comfort living, that evolves as a by-product of the work of corporations. V.CIVIC ENGAGEMENT Technologies have changed the process of civic engagement. They not only changed the channel for transmitting, they changed the whole process of participation. Open government promotes transparency, accountability, and citizen engagement and recognizes that Web 2.0 technologies allow stakeholders to access information and collaborate online as never before. VI. COMPLEXITY Creating tightly-coupled systems leads to high efficiency and, because the system integrated in such a complex way can fail in an unpredicted way, one part failed causes a cascade effect on all other elements.The system becoming more dependant on the intelligent software gets harder to fix manually if something goes wrong. The more complicated the infrastructure we put in, the more the damages cost.

open data movement along with activists. Why do they do it? Open information gives huge opportunities to multiply the profit without enlarging spendings. Providing access to technologies for those who hadn’t before is another trend that is supported by IT companies. So, great development that happens in this sphere has commercial roots and comes as a by-product of corporations’ will to gain profit. It’s very important to think whom we are supporting by promoting one or another initiative. So, how smart is too smart? Perhaps the problem is not at the smartness itself but the pace of implementation. In that sense, it seems as for current Moscow instant smartness is not the preferable option. That’s not because there is no value in the techno-aids in our urban environment. On the contrary, the issues that make us hold back lie in different areas. First, it is the question of place. The solutions we researched come as ready-made products, not taking into consideration the specific context. In addition to that, it seems the wrong priority in terms of budget investment. The step into technology for Moscow, for the moment, appears to be fragmented and problematic, as the errors demonstrate, and technology is used as a medium of branding the city rather than improving it. Last but not least, it is the issue of governance that seems to be a high priority, but also highly problematic. The dysfunctional system that denies the release of its information, if it is not for the sake of investment, calls for a reform that goes beyond the digitization and into the core of building a trustworthy system.

r e fer e n c e s 100 Smart Cities Worldwide, 2010, Nikkei Business Publications, viewed 3 June 2013, < http://www.nikkeibp.com/news/100927.html> Abyzov M, Joining “for show” we do not need, 2013, Open Government of Russia, 21 May, viewed 2 June, <http://xn--80abeamcuufxbhgound0h9cl.xn-p1ai/blogs/post/5508049/> Angelidou M., Tarani, P. Branding for Smart Cities, proceedings of the 1-st Pan-Hellenic Conference on Place Marketing and Branding, Department of Planning and Regional Development, University of Thessaly & Imagine the City, 30 March - 1 April 2012, Volos, Greece. Banavar G. (cited in Chapman G., 2010), IBM pitches ‘smart’ cities as planet savers, 13 December, viewed 2 June 2013, <http://smarteconomy.

o b s er vatio n s

typepad.com/smart_economy/2010/12/ibm-pitches-smart-cities-as-planetsavers.html> Budget expenditures in Moscow, 2013, Open Budget of Moscow, viewed 2 June 2013, <http://budget.mos.ru/gp_expense> Centre of Regional Science (SRF), Vienna University of Technology, 2007,

Despite all this, no critic should be dismissive in a totalitarian way, as even in dysfunctional examples there can appear positive elements worth implementing. For example, bottom-up initiatives and the process of civic engagement in the decision making process are inevitable agenda of today’s government policies. Big international companies promote

Smart cities. Ranking of European medium-sized cities, viewed 2 June 2013, <http://www.smartcities.eu/download/smart_cities_final_report.pdf> Coca-Cola Sees Similar Investment Risks in Russia and Nigeria, 2013, The Moscow Times, 28 February, viewed 2 June, <http://www.themoscowtimes. com/business/article/coca-cola-sees-similar-investment-risks-in-russiaand-nigeria/476137.html> Cohen B., 2012, The Top 10 Smart Cities On The Planet, Fast Company, viewed 2 June 2013, <http://www.fastcoexist.com/1679127/the-top-10smart-cities-on-the-planet>

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Corruption and Human Rights in Contemporary Russia, 2012, INDEM

like-big-brother.html>

Foundation, viewed 2 June 2013, <http://www.demokratia.ru/docs/?con-

Smart Cities and Communities Communication, 2012, European Union, viewed

tent=doc&id=19>

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<http://www.usa.


p r oje c t THE RUSSIAN PROGRESS AND TECHNO OBSESSION HAS PROVED TO BE FATAL IN NUMEROUS CASES. RIGHT NOW, WITH THE NEW SMART STEP PENDING, THE WINDOW TOWARDS THE NEW SERIES OF CATASTROPHES IS OPENING. BE AWARE, YOU ARE ABOUT TO GET SMART!

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B E R L IN DON’T TRUST THE DATABASE! GEERT LOVINK

SAN F R A N CIS C O THERE IS NOW A WINDOW WHERE ONCE THERE WAS ONLY A WALL. BEN CERVENY

LONDON YOU CANNOT HAVE SMART CITY JUST BECAUSE YOU BUILD A LOT OF SMART BUILDINGS, TO ME SMART CITY IS A SPACE WHICH IS BUILT BY SMART CITIZENS ENGAGED IN SMART SOLUTIONS. MARA BALESTRINI

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RC: He was seen as a guru for computer scientists.

On infrastructure, technology and cities An interview with Felicity Scott

Re(Charge) Information/RC: Looking at the different ways technology is impacting cities today, how do we, as architects or researchers engage, or engage otherwise/operate from within that system, and how has this issue been approached in the past? Felicity Scott/FS: The question of how increasing information was becoming a part of surveillance and control technology was something already creating anxiety in members of Archigram in mid 1960s. This has a long trajectory of how architecture has been dealing with the control of society. I have always been fascinated with Ant Farm, as an experimental architecture group. One of their key gestures was going to Xerox Park; today, they would have gone to Google, just like you guys. They went to IBM, NASA, went right to the heart of the beast to understand the shift from industrial to post-industrial and informatic technologies and incorporated that into their work. They made these arguments about wanting to engage the media, because it was the dominant force in organising the social and the environment in the late 1960s. This was the necessary point of engagement for a form of architecture, unlike a lot of experimental practices that disengaged. Their response was precisely through engaging informatics, in their case videos, from the first moment the Sony Portapak was available to the general public. They had lunar rover in an exhibition in 1973, so they played on exactly that paradox of whether they were radical, or something very different, in terms of their way of engagement. This is something that would have been

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something entirely antithetical to earlier avant-garde practices of negation. I model this problem historically through that time practice, to understand the contours as much as anything, the dynamics of these sorts of strategies. RC: Is Christopher Alexander still relevant or interesting when we talk about ‘complexity’ and ‘emergence’, topics that are becoming quite popular when speaking about cities today? FS: He tested out his systems-based thinking was after he got a job to test out the BART, the Bay Area’s rapid transit system. This was the moment at which he shifted from his tree structure to his semi-matrix structure in attempt to figure out a different type of complexity. Despite the enormous reception of Alexander in the late ‘60s, I think it is also interesting that it appeared in the first volume of Zone magazine in the early ‘90s, and is articulated in the thinking of Gilles Deleuze and Felix Guattari, and also not unrelated to Virillio in interesting ways. To stay on track, the question of why in the early moments of thinking about parametrics and architecture, these characters matured to a type of visibility, offering a different paradigm for architectures. With Alexander, I find too essentializing to be a good model. I think the questions he was asking were interesting, the models he proposed a bit problematic. Virillio was a figure who remained in the realm of problematisation. He was actually testing material thesis.. working on his pendulum-destabiliser project in Nanterre in ‘68 when the riots broke out. I don’t know.

FS: This is what’s so funny. The fantastic paranoia in Virillio, which I appreciate a lot, is not pro-digital, hence the intense question of warfare, the militarisation of the environment, bunker archaeology, this long trajectory of thinking of the relation between military technologies and urban form that he is updating in his texts. I think Virillio is a better interlocutor to be with around these questions than somebody like Alexander, who is not an interesting character at all, but yes, you are right that he generates the language and articulateness with which he engaged in these new forces. A large part of their reception was techno-euphoria, not a questioning. RC: But he is trying, like Lynch, to understand the whole pattern. Alexander said that if we study carefully different parts of society we can say, ‘ok these people, they do this and that.. so it should contain these elements for them..’, like he did in a project where he went to Lima, Peru and lived for 3 months. FS: The question that needs to be posited is what type of update. How do we think of these terms in a condition where the circumstances have radically changed? To what degree are their polemics even legible to us, and, if they are legible, what would be the equivalent nexus of concern? For instance, the social, technological, political, material or aesthetic, that we would need to think through in the present. So this is why the formal appropriation, or even the formulaic appropriation of something, like systems logic, and the semi-matrix is not the answer, but the provocation to the answer. I mean otherwise, and I’m not accusing anyone of this, that you fall into the same kind of trap that historicists, and post-modernism tends to make. This is the distinction one needs to make. How the


architect got traction, in the particular condition in which they were working and recognised a certain set of symptoms as they haunted the field at that time. RC: Which architects were trying to understand infrastructure? FS: Certainly all the Team 10 architects, when they started to talk about mobility, communication, they were channeling debates on infrastructure. On the other hand, they might not speak in the same way as people in the ‘90s spoke about infrastructure. It’s a different discourse, for example, with Kenzo Tange and the Tokyo Bay plan, and all of those that started to think of architecture as systems that operate in different temporal modalities, and different degrees of permanence, but I don’t think they took on the city as a project. RC: And urban research on that aspect. So who was specialised? The territory of urban research is so subjective, so what can you actually say? FS: When you look at Virillio’s early work, The Insecurity of Territory came out in 1974, and, you know of course, he was sitting in on Foucoult’s lectures at the College de France and thinking of paradigms of governmentality, and management of populations and territory. Virillio was a thinker but also a protagonist. This doesn’t get to the question of the subway, but Archizoon’s No-Stop City speaks to these questions: on the condition of the city, of it as a communication system. This is a crazy reference maybe, but in 1960, when Bernard Rudofsky first came back from Japan, he was asked to do a set of exhibitions at MoMA, and everybody knows Architecture without Architects from November 1964, but the first 2 exhibitions he did was (sic) first on stairs, and the other on roads. I also mentioned ’64 because that was the year Arthur Drex-

ler did the famous exhibition, 20th Century Engineering, that shifted from the architectural object to infrastructure. But Rudofsky, who always operates in this allegorical, difficult… apparently stupid, but quite smart, register, had these two categories of roads. One on the ground, and articulated them as roads that form as infrastructure of imperialism. But then he also has these other roads that left the ground, from the Fiat factory to any number of utopian projects. Underlying all this was a thesis that he later revealed as the inroads of all these other systems of infrastructure. For a man of his generation, totally overcome by anxiety, these questions totally played out. RC: As a historian, where do you see things heading in the future? FS: I’m not a futurologist, but one always hopes that history is not seamless, and things will always interrupt the current narrative. Even characters like Buckminster Fuller, or even Archigram, when they write about their image of being able to talk to friends via TV, which we now take for granted, like what was science-fiction in the 60s, the degree to which that was realised, and then immediately naturalised in terms of its reception - even things that we might think of as totally crazy might take place. It gives us a moment of pause in a productive way, to review what’s actually happening, in our use of it, and not to refuse it, but to produce a type of critical self-consciousness with regard to the use of technology. This is what I feel architects can bring to the table, not just producing ever more sexy forms.

Felicity Scott Associate Professor of Architecture, Graduate School of Architecture, Planning and Preservation, Columbia University, and Director of the Program in Critical, Curatorial and Conceptual Practices in Architecture.

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“We still have a fantasy, some kind of a fridge that orders itself milk when it runs out” Christian Nold

I see all this data collection happening now as a way of re-experiencing or reframing of the environment. You can find patterns in all the data that you have collected in Twitter, biodata, foursquare, but the main question is what you are going to do with that? Imagine you have the whole data in the world in real time, absolutely everything, what would you do? Imagine you have perfect information, about anything and everybody in the whole universe in real time, of course this is fantasy, so what? And where do you start? You will have all sorts of problems. From how data is gathered, you make choice (sic) of what is important. I had a friend that basically did not get a job because she did not have a Facebook profile, and they could not verify whom she was. It is strange, no? Imagine, in five years time, if I do not tweet, then I lose my card points?! How should governments and institutions interfere? You could just talk to people and see what they care about. The level of Intervention is a difficult one.   I am trying to develop tools that allow people to articulate something about their experience in a different way using measuring devices. So, we developed the things that allow them to measure noise and finding (sic) alternative ways of representing things. So, there is not a noise that they are experiencing – it is about representing experiences in a different way. Advertising companies wanted to redesign, rebrand emotionally

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the whole city, for example, BMW that (sic) wanted to look at stress levels of drivers. The general metaphor is that everyone wants to cut the head off and see what is going on inside. With smart cities we are completely at a mess with crazy technologies and are manifesting control fantasies, with a lot of exclusions and technologies where there is no rationality.

initiative. I think we need to build things for groups of people. I think we need to look for alternatives. There are mental alternatives but also physical alternatives. I think they are generating really interesting data. These are the datasets that could be interesting to look at. They have happiness in the whole of America. Happiness is not abstract, it is about things. Homelessness is a very interesting political issue, and it is not surprising that homeless people do not have smartphones to tweet about all these things.

I just do not think the ‘smart city’ is good for anybody. I think, generally, it is really bad, almost in any sense it is bad! I think it leads to a waste of money, a waste of energy and a lot of nonsense. I think there are some real problems like oil running out, and climate change, social issues and so on. And something like the ‘Internet of Things’ does not address any of the key issues. We still have a fantasy, some kind of a fridge that orders itself milk when it runs out. We should have realities based on what we have right now, that try to deal with real issues. It does not have to be a solution; it could be autonomy in people’s lives. Bicycles are autonomous technologies and it has not really changed in hundreds of years. The ‘smart city’ is not a new idea, we have had this idea for (sic) last twenty years, and yet have not realized it because, I think, it does not have a real value and is a stupid idea. We do not have it because it is not a problem. There are real problems that need to be addressed. I think we could build a smart city and we could make it as a bottom-up

Christian Nold Artist, researcher, educator, founder of Softhook Design, a cultural design agency, spoke with Artur Shakhbazyan, student of (RE)Charge Information Studio about the concept of the ‘smart city’, the Internet of things and technology. He strongly believes that we can gather completely new types of big data and use it to improve urban life.


On GAFFTA The idea was to represent artists who work with code because obviously San Francisco is the global epicenter of technological innovation. Many big technology conversations are happening here and lots of money, and opportunities that attract entrepreneurs and young artists. It’s a secret but we started GAFFTA after a techno party, and I see my personal task akin to a dating service for San Francisco, as there are lot (sic) of active communities and I make them work together. That’s my duty to the city. We have no choice apart from being grassroot but from there comes lots of our strength. We have the most pivot because we have a community that immediately responds. We are casual (sic) organisation with a very serious mission. We operate in-between this universe of art and technology, but, in field (sic) that faces public technology, it’s kind of a dirty word.

On impacting the city and urban life Many of our projects are great in terms of being great prototypes but we determine success in terms of adoption, and that’s a big challenge all over the world. The main problem is in its implementation, and this requires a lot of work alongside city officials to be realised. Even when we propose exact projects that will save them money and will obviously improve the city experience, it takes so much time to pass them. We haven’t successfully done that yet, so it would be a measure of our success if realised. It says not about the quality of projects we propose, but about the nature of government. We’re still pushing for it but it has yet come to even proper discussion. At the moment, it seems like solutions can only come from the private sphere.

The ‘California Ideology’ The real conversation is how you can work with private systems but not what is discussed at all data and technology

Big tech, data-driven initiatives, and the nature of government Matthew Dryhurst

conferences. Big tech might be improving things in life but not necessarily altruistic (sic). Decisions in a city like San Francisco have something to do with big money and big technologies. Conversations are accelerated because there are financial opportunities. And they talk about ‘communities’ and ‘urban projects’ and about ‘making streets a little bit better’. That’s a nice way to deliver conversation but I don’t believe that any private company has any concern about beauty or aesthetics, so I see art and social issues as a very convenient line in order to push greater objectives.

an impact on something. My hope is to bring people to a level of code literacy but not to turn them into data scientists. In San Francisco, we are reaching a time where if you want to be employed, you need to have at least a basic level of coding.

On education As we are situated in more economically depressed areas in the city, we started working on local specifics. We tried to bring in people from different projects that can impact their immediate environment. We have wonderful universities here but it costs $40 000 a year to attend, so it is certainly not for everyone. We offer graduate level classes for less than $20 an hour, cheaper than community college. We are not career-seeking academics that teach in classes. The learning process is guided by people who have actually created something than from a tutor (sic). Students learn about technology from its creators, which we feel is far more responsive. The teaching staff constantly circulates, so knowledge becomes more relevant. We bring in students who do not have prior experience in coding and teach them the fundamentals so they can take part in hackathons. We want to produce people who go from nothing to become hackers in a couple of months. We teach them until they have some skills to make

Matthew Dryhurst Public Programme Director and Founder, Grey Area Foundation for the Arts, San Francisco.

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Cyber-War Capitalism & Data Religion An interview with Kazys Varnelis

Re(Charge) Information/RC: Tell us about work and approach taken at the Network Architecture Lab in Columbia University and at AUDC, your ‘speculative architecture practice’. Kazys Varnelis/KV: AUDC speculates with different data and different techniques, and the Network Architecture Lab perceives things, not similarly, but in a parallel manner. It is always a question how can I combine these two things (sic). In neither case am I very interested, for the most part, in questions about how we use data in a hard quantitative way, sometimes we will for some reasons but that’s not the primary drive. I see myself as an analyst more than number cruncher. I am not very interested in data visualisation, which is certainly important, and people can do it, but at the same time, it can lead to a very simple reading of data’s role in our lives. I feel that increasingly today, in architecture schools there is a trend towards a very direct idea of representation of a kind of a transparency of representation. Even though I love the building, the Seattle Public Library is a great example of this. You can see from its diagram: here is the site, here is the program, we can move it around, we express it and we build it, but it’s more than that. I love the building in many ways but in the same time that kind of mentality that comes out from a lot of MVRDV’s projects, this kind of belief in datascapes has been something that seems natural when in fact data is completely shaped by our interests. RC: Are these beliefs articulated in your projects?

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KV: Right now, AUDC is doing a project on the work of Stanley Milgram. He was a psychologist, he was teaching in Yale, he was very important in the 1960s. He supposedly developed the idea of the five keys of separation, that we are only separated by 5 degrees from everyone else in the world. And that idea is something we are taking for granted, it’s part of social network theory, which is now considered a science. And yet the curious thing about that experiment was that actually the data is almost completely wrong. Specifically, Milgram’s interpretation that got published isn’t supported by the data. It was supposed to be a world in which all he could do is he would drop these letters in the middle of the United States, and it was supposed to go to a random person who would pass it on to another person and they would have to pass it on and so on and so forth. So lets say that I want to reach Norman Foster, I would see who I know someone that might know him, or might know somebody in his office, etc., that kind of mentality. But of course this was not about architecture, this involved a much broader audience. In Iowa, these people were farmers and had no knowledge of who a random person in Boston was. The premise was that it took an average of 6 hops or five degrees of separation. The reality is most of the letters never arrived, by far, at most only 30% got there - Those that got there were largely sent not to random people but to stakeholders in Iowa. So the whole thing was essentially a fraud but the thing that is revealed in this project is only partly what AUDC is doing, which is about psychology and how it manipulates us, but it also reveals

that the data isn’t transparent, and that in the data, something is manipulated very often. RC: Apart from manipulation, there is also the intentional obscuring of data, and the whole world of classified data. KV: This morning I was talking to someone that runs a very large company of understanding these infrastructural aspects of the internet, again using data, and even for him, a man who is totally working in a very hardcore business project trying to understand infrastructure using data from major corporations, governments, the legal issues and the kinds of thing that are hidden are huge, which leads us to another thing. The US government produces even more than that data every year that is classified. And we can probably argue that every major country produces more data that is classified than is published. It’s probably a reasonable assumption that most of that will probably never be unclassified. And much of my work revolves around trying to deal in data, not in the hard sense, but to understand our relationships with it. In a way we have a religion of data I think, a religious belief in it, a belief that if we can find the data for something it must be true and yet it’s the political issues behind it, the social implications, the legal issues often shape data in ways that are very specific. RC:I was wondering about the datascapes you were saying that are not natural. KV: Roland Barthes, in his book Mythologies talks about our desire to naturalise certain things, and the desire to believe that certain things are obvious and true. The internet is a force of freedom and liberation, that data is evidence or that data is true. What I am suggesting is that humans construct the data we choose, generally speaking, and how


it’s constructed is crucial. It’s often presented as, ‘This is it, This is the future of the city. It will be this based on these projections’. Well, what are the assumptions and why, and who benefits? One of the things Blue Monday is talking about is our collective desire to voluntarily commit to media, to believe in media, and to want to be part of it, to give ourselves up to everyday surveillance online. Companies like Amazon would make George Orwell or the KGB embarrassed. RC: What is the role of people in this environment? KV: The human is no longer important, a person is just there to make a decision and the algorithm takes over and everything is happening in these buildings. It doesn’t matter where they are, where servers talk to servers, and this is happening in milliseconds level. It’s like finance itself is becoming part of the cyber war as well and what’s really important too that is that data is being seen as this friendly thing though its a crucial part of this process. We are in a new era of war, and it is as important as the Cold War but it’s actually much hotter in a sense. Things are happening constantly now to the point that corporations are engaged to them. Capitalism used to be very simple, Karl Marx and Adam Smith would both agree that capitalism was a question of somebody with a lot of money invests in something and gets more money back, all that. We know where that goes, but today it’s almost like cyber war capitalism RC: Do you think that there is a real value in data and its ownership? KV: I suppose one of the questions is what can we do with it? What are our rights to this data, what is our relationship to it? I think that certainly the data can be useful, we just have to be careful to understand what we have access to and what we don’t have access

to. What we may see may be a tiny fragment of what’s really there. For example, in the smart cities project, there is a real difficulty for us to get access to the data that matters, and you know corporations and governments do have access to this, so why is it that we cannot have access to that data? There is some kind of opaqueness, and then, when you start pushing for it, you find out that whoever you are talking to, be it governments or corporations, they are just there, right on the other side of that data. RC: It is very interesting that we were visiting an urban center where they try, through science, to find ways of extracting data that would be useful to sociologists, but without asking any people. KV: It might just be that we have to live in this other world, especially when we’re getting to the point that we’re doing this real time. I think it will change as we are already are giving up so many things about ourselves. And so what, so what do you learn? So they know what I want to buy or what I think, ok, so what can you do with that? Maybe not much, but I think there is a role for ‘big data’. However, I also think that in the way that is being used now, is for the cities, in many ways, to prove things that people already know But do we have accustom ourselves to total control or have we made believe that there can be something better in society, or do we just have to say ‘this is it, this is our contemporary condition’, and we just have to deal with it? One of the things we talked about in Blue Monday was religion and it seems to me that this condition is almost like a new religion, where you believe you give yourself up to something. When you give up your data and its like you’re giving yourself up, you believe in this thing and its power. And of course when you look at these things (points at an iPad and iPhone), the interface

design is magic; it’s designed to be magical. Of course religion has always been about connecting with others, not being alone, and being part of something bigger. RC: But maybe absolute transparency would make governments, or people, or whoever that gives up data just invulnerable. The end of data journalism - when governments would expose everything on their own, is it good or bad? Probably total transparency is the future we are going to… So I guess the question is, is it possible to reach any total transparency, some kind of utopian future? KV: Dystopian! Well again isn’t one’s idea of religion, that the future is the afterlife and being able to see everything that goes on here, as a ghost walking into people’s room when they’re having sex or something? Somehow it’s part of it, the desire to give one’s self up. There is a desire to be absolutely transparent by many people. A rush towards doing so and hoping to become part of something great and even if you are not thinking of that consciously. But that hope is also becoming part of the media.

Kazys Varnelis Director of the Network Architecture Lab, Columbia University, and co-founder of the non-profit architectural collective AUDC and co-author of ‘Blue Monday’(Actar, 2007).

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