KNOWLEDGE ECOLOGIES Stephan Sigl
KNOWLEDGE ECOLOGIES Stephan Sigl
Master Thesis submitted in fulfilment of the requirements for the degree Diplom-Ingenieur to the Leopold-Franzens-University of Innsbruck Faculty of Architecture Supervision Univ.-Prof. Dr. Claudia PASQUERO Co-Supervision Maria KUPTSOVA, MA Institute of Urban Design - Landscape Architecture ioud / synthetic landscape lab Innsbruck, August 2020
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PREFACE
The conditions how knowledge is being accumulated, understood, interpreted and applied is subject to a perpetual change. Artificial Intelligence currently pushes means and methods for the development of autonomous, intelligent machines. It seems that every aspect of our life and environment faces rapid modifications. So how could a proposal for a future knowledge environment get along without the ability to adapt radically? Digitisation affects all areas of life. The quantity and quality of accessible digital data is growing exponentially. Conventional data Storing consumes huge amounts of energy and space. And it seems likely, that capacities will run out. At the same time, ground-breaking technologies such as data storage in DNA strands are appearing on the horizon. (see: Ceze et al. 2019) In the foreseeable future, this may not even require laboratory space, since data can also be stored in living organisms. What could be more obvious than to conceive of Knowledge Ecology as a landscape, in the open air?
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Pr o p o s a l
This Proposals shows in a first step an essayistic specu-
of reframing traditional approaches of future knowl-
lation of a distributed autonomous information storing
edge environments. Speculative thinking operates as
and processing machine that is inherent in an enig-
a tool for undogmatic visual prospects. The complexity
matic terrain, partially created by its own intelligence.
of society, science, economy and technology in this
In a further step the sampled results are tested and
context could seem to us to be an almost impenetra-
applied on a specific site that is strongly transformed.
ble matter. This is precisely why the thoughts of Dennis
The redesigned landscape stands for an aesthetic
Gabor, the inventor of holography, is particularly
reflection of a virtual landscape of the mind, which
appropriate here:
should make knowledge spontaneously and openly accessible, perhaps with the help of augmented reality devices.
“The future cannot be predicted, but futures can be invented. It was man’s ability to invent which has made human society what it is. The mental processes
The connection between man and machine is con-
of inventions are still mysterious. They are rational but
ceived here by referencing from the address coordi-
not logical, that is to say, not deductive.�
nates of a city to the virtual level. Addresses, in turn,
(Gabor 1964 207)
are each a reference to a location where humans can be found. As coordinates, they outlast any structural change, so to speak.
Thus, on the basis of aesthetic manifestations, an understanding of future needs and possibilities in con-
This conception of knowledge ecologies may be a
nection with the acquisition and transfer of knowledge
proposal for an antrophocene - framed environment
could be considered. The goal must be to make
typology, analogous to the basic idea of archives and
knowledge and its acquisition accessible to all people,
libraries. It is an aesthetic design conception for neural
both informally and spatially. Editing and control of
networks and their interface and storage structures on
knowledge needs many participants as well as a
a landscape scale. In a way the conceived design
culture and spaces of discourse. Some of these rooms
may appear thoroughly speculative for the purpose
might be virtual in nature.
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Preface Contents Proposal [A] THIRST FOR KNOWLEDGE KNOWLEDGE MILESTONES CASE STUDIES
[C] AN ESSAYISTIC SPECULATION EMERGENCE DISTIBUTED NEURAL NETWORKS EVALUATION THE MACHINE AND THE UNCONSCIOUS
[B] DIGITAL TURN CONTEMPORARY KNOWLEDGE STRUCTURES
[D] APPLICATION ON SITE MORPHOLOGY
SIGNIFICANT FACTORS
EVALUATION
DNA DATA STORAGE
DISTRIBUTION GRANULARITY INWEAVING HUMAN AND NON-HUMAN [E] SOURCE REFERENCES [F] APPENDIX
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[ A] T HI R S T FOR KNOWLEDGE
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collaborative aesthetics ethics natural artificial exterior interior human-centered
non-human human
knowledge accumulation and transfer cave painting, oral, books
urge for knowledge
basic human characteristic
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arts
interpretation and expression of Knowledge
subject
exploring discovering
1450 Gutenberg letterpress printing
development of sciences rational thinking
mundaneum
Jorge L. Borges infinite library
technological development technocratic thinking
libraries universities
computation machinic processing
server room: similar typologies
digitization digital storage
Knowlege Milestones
collaborative aesthetics ethics natural artificial exterior
interior human-centered non-human human
voyager project golden record
seed vault infinite monkey theorem computing in place of storing
science & bio-tech progress dna-storage, big data, AI computation capacities digital turn parametric design
reframing anthopocenic strategies
the unconcius of the machine
farming
bio-computing
distributed computing organism
knowledge ecologies
energy extraction
transfigurated campus
integrating interior and exterior
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fig01: Le RĂŠpertoire Bibliographique Universel vers 1900 Author: Patrick Tombelle
fig03: Svalbard Global Seed Vault, Spitsbergen Author: Svalbard Global Seed Vault, Matthias Heyde
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fig02: Voyager Golden Record Author: NASA
C a s e St u d i e s Knowledge Machine The Mundaneum, called as “Google de papier” by Le Monde (see: Mundaneum website 2020), was established by the Belgian librarian Paul Otlet in 1889. This is the early and fascinating attempt of a universal knowledge transfer system, which shows some similarities with today’s tools of the web. “In 1895, Otlet and La Fontaine (...) began the creation of a collection of index cards that would reach more than 15 million entries. Later Otlet set up a fee-based service to answer questions by mail, by sending the requesters copies of the relevant index cards for each query.” (Wikipedia contributors 2020, May 15) Voyager Project The Voyager Project is an example for transferring. It´s a story about an exploring spacecraft travelling through space, but also carrying data intended to transmit to extraterrestrial life. The Voyager Golden Records are two phonograph records that were included aboard both Voyager spacecrafts launched in 1977. The records contain sounds and images selected to portray the diversity of life and culture on earth, and are intended for any intelligent extraterrestrial life form who may find them. (see: Wikipedia contributors 2020 August 01) Seed Vault It´s a story about storing gene information of plants for future generations. The Svalbard See Vault is an underground facility with ideal conditions for the long-term storage of rare seeds. The aim is to preserve the biodiversity of plants. Rare duplicates from seed banks all over the world are stored here as a backup. On the remote island of Spitsbergen in Norway, it is hoped that these specimens can also be preserved in view of the threat of natural hazards worldwide. (see: Wikipedia contributors 2020, July 03)
We humans always have been driven by a thirst for knowledge. There are some milestones in history, at least seen from today’s rational view of the world. This diagram on the previous pages shows some interconnections of milestones regarding certain attributes and subjects. From the oral transmission of information to the printing of books a lot of time passed, from here the growth of information increased rapidly until today. The Big Data age is leading to a similar information explosion with completely different dimensions. The case studies cited show how deep storing and transferring knowledge is an everlasting necessity in human life. Man has the desire to explore the universe and at the same time to present himself, to hand knowledge to descendants or even extra-terrestrial life, bringing knowledge to immortality. Knowledge includes communication, storing and transferring, among other issues.
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[ B ] D I GI TAL TUR N
“With different nuances, ... the second digital turn in architecture is largely about finding new ways to design, ...� (Mario Carpo, 2017)
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Ethics Aesthetics Exploring artificial
Server Farms Library
KNOWLEDGE Generated Landscape
Typology Evaluation
natural Archive
Transfer
Transformation
Distribution
i interior exterior
Essayistic Speculation Void Reframing Parallel computing
Access
Editing
DNA Storage
subdivide Augmented Reality
KNOWLEDGE ECOLOGIES
Undogmatic prospects Partizipants Displacement
non-human
h Workbench
Elevation Big Data
Workflow
Space
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Erosion
Application: Site
Growth E Energy
locations: campus/lib b
shortest path
Resolution
DIGITISATION
Granularity
Artificial Intelligence
Theory vs. Formula human
ECOLOGIES
Digitization of books changes workflow One aspect of digitisation is the full-text digitisation of books and since all these texts are available digitally, not only humans - also machines can read and understand them. Moreover, these data are accessible independently of time and place, which calls into ques-
“In order to understand and
tion the need for space in libraries. But the demand
chronicle the emerging con-
for physical library space seems unbroken, as Graham
dition that the data centre
Matthews, British Professor of Information Management
embodies, we will push open
states “ … at the same time, there has been a great investment in university library space both before and
the pressurised doors and cross the lines of the human
since the millennium, with major projects in England
exclusion zones to trespass
…” and “...elsewhere in the world...” (Matthews 2013).
through the machine land-
The digitalization of information has radically changed
scapes that run the world.” (Young 2019)
the way we work with data. Instead of a linear work with physical papers a complex and multi directional workflow has developed.
If the Tools change, the workbench
Big Data and AI
has to change as well.
Big Data not only stands for an awful lot of data, it
Conventional storage of large amounts of data
also stands for very clever methods of combining and
consumes large amounts of energy and space. Digital
evaluating information. And it’s more about calculat-
data is apparently dematerialized, its resource require-
ed correlations and probabilities.
ments prove the opposite. It seems likely, that capaci-
(see: Mayer-Schönberger 2013)
ties will run out.
Powerful computing technics, such as parallel computing or quantum computing are very efficient and
So the consideration to connect the archives with
powerful in comparison to today´s classic (serial)com-
environment is charming. By now, architectural typol-
puting. Although quantum computers are not yet able
ogies are similar (grid, raster-based), baroque library,
to perform all the calculations that classical computers
modern archive or server room: their design principles
can do, it is assumed that quantum computers can
didn´t change in the same range as the digital shift
solve many problems faster. (see: Wikipedia contribu-
would demand. In addition, server rooms are basically
tors 2020 August 02).
pure machines, as Liam Young notes:
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This leads directly to an improvement in artificial intelligence: “Today, the learning curve for machines appears to be sharply steeper than it is for human beings, which is fundamentally changing the relationship between humans and machines.” (Ramge 2019) Through growing capacities of computed calculations storing of data could become obsolete. Information could be calculated in real time, based on formulas, algorithms. Data storing remains a subject of development. In 2018 Word´s total data adds up to 33 Zetabyte. And will rise to 175 zetabyte in 2025. (see: Reisel et al. 2018) “If you could download the entire 2025 Global Datasphere at an average of 25 Mb/s, ... , then it would take one person 1.8 billion years to do it, ...” (Reisel et al. 2018) It is likely that capacity will eventually run out given the current production of data. Growing amounts of data require improved methods of storage. How does Knowledge differ from Data? In his short story “The Library of Babel”, first published in 1941, the Argentinean writer and librarian Jorge Luis Borges tells an atmospheric story about the inhabitants of a library of infinite dimensions. The library consists of an infinite number of hexagonal rooms of always the same size, which in turn are always equipped with the same number of books. The content of the books consists of all possible combinations of 25 letters or punctuation marks. This means that in the infinitely large number of books, among all the seemingly meaningless combinations, there are also all conceivable literarily meaningful combinations in the volumes. “All - the detailed history of the future, the autobiographies of the archangels, the faithful catalog of the Library, thousands and thousands of false catalogs, the proof of the falsity of those false catalogs, ...” fig 04: Infinite Monkey Theorem Author: New York Zoological Society
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(Borges 1998)
Si g n i f i c a n t f a c t o r s However, it is very difficult - and the inhabitants of this library have been trying for generations - to find the intelligible ones in the infinite number of books. The inhabitants are aware that they are sitting on a great treasure, which is fatally not easily accessible to them. Even the catalogues, in which the locations of the meaningful works would be listed, are tragically not to be found. (see: Borges 1998) What could be more Today the use of artificial intelligence could probably
obvious than to conceive
help us out of this mess if we were the inhabitants of
of Knowledge Ecology
such a library. In fact, we no longer need to imagine
as a landscape, in the
such a library today, consisting of printed books. Basi-
open air?
cally, all we need is an incredibly powerful computer that simply tries out all the letter combinations and, with the help of programmed intelligence, stores the meaningful combinations. Infinite monkey theorem Not quite dissimilar is the idea based on the infinite monkey theorem: If a monkey had the opportunity and an infinite amount of time to randomly type letters
We are talking about huge amounts of data.
on a typewriter, after an infinite amount of time he
Conventional storing (magnetic, oprical) consumes
would have produced all meaningful and meaning-
huge amounts of energy and space.
less texts, even “translated� in all languages. The task
Digital information can be encoded either as a se-
of separating the useful from the meaningless would
quence of 0 and 1 or as a sequence of letters.
also be challenging here. For this, one would probably
In laboratories, digital data can now be stored directly
need an infinitely long period of time again. This the-
in the molecules of the DNA after it has been encoded
orem is based on the Borel-Cantelli-Lemma, which is
using the 4 letters of the nucleobases of DNA.
part of the mathematics of probability. (see: Wikipedia
This also works in the molecules of living organs.
contributors 2020, July 10)
An existing DNA strand is taken from an organsim, copied several times, recoded and inserted into a DNA
But these considerations seem to be particularly
strand again. Data can continiously be read wirh DNA
fascinating today, in a time when we are learning to
Sequencers. The data-structure never changes.
handle very large amounts of data. Will it perhaps one
If DNA is damaged, error correcting codes are im-
day be possible, for example, to anticipate important
plemented to restore data. This happens in a DNA
research results by simply artificially producing scien-
sequencer, mainly automatically. (see: Ceze 2019)
tific articles in which they are to be published without
The sequencer is virtually a black box.
having done any research at all?
In this proposal, it is a pure machine.
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D NA data stora g e
Exterior DNA storage in transformed landscape as a distributed system of Knowledge Ecologies
A (Adenine) C (Cytosine) T (Thymine) G (Guanine)
01 11 10 00
A C T G Sequencer //encoding
interior
(source information see: Ceze et al. 2019)
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storage density low
storage robustness
high
energy input
in vitro storage
in vivo storage (living cells)
extremely high
exterior
very robust very low
01 11 10 00 Sequencer \\decoding
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[C] E S S A YIS TIC KN O W L ED G E EC O L O G Y
„At the moment when the electronics revolution seems about to melt all that is solid - to eliminate all necessity for concentration and physical embodiment it seems absurd to imagine the ultimate library.“ (R.Koolhaas, Strategy of the Void)
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This leads to the essayistic speculation of a generic Knowledge Ecology, based on elements of these changes. A catalogue of generated landscapes which are transformed by massing tools, displacement, distortion is formed. Iteratively and due to the needs of the system. Starting from an appropriate geological field, 1000 x 1000 units, in convenient atmospheric conditions, the system creates its own terrain, which is subsequently exposed to natural processes like aging and erosion.
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Morphogenesis
thermal and hydro erosion embankment vs. excavation geolocical transformations dry / humid hot / cool calm / windy wind erosion biogenic sediment accumulation
eastern wet side high wind forces heavy erosion
atmospheric and geolocical forces according to prevalent conditions
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fn:20191105_cat_0E geo 0E erode 1: hydro thermal freeze@20 erode 2: hydro + thermal water flow + TpVw
fn20191104_cat_0Aa geo 0Aa erode 1: hydro+ freeze@40 erode 2: hydro + thermal TpVw
fn 20191104_cat_0A geo 0A erode 1: hydro freeze@20 erode 2: hydro ++ thermalHF distortion: swirl TpVw
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Catalogue
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speculation about condition below the ground level through further erosion simulation
surface investigation through granularity
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swamp-land network: foamy sponge rather than grid
disintegration: component parts of equal size
Eva l u a t i o n s
The landscape is being evaluated with tools like further scaling or reframing by interpretation. Details below the surface sediment can be interpreted as substrate containing repositories, as environments in which organisms live. Branching structures provide nutritive substances. Cell bodies of neurons are insinuated.
base terrain
redrawn segments 01
r e dr a wn s e g me n t s 0 2
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Iterative steps of massing and transforming of parts feed new specualtions about surface and conditions
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Sp e c u l a t i ve m i c r o s c a l e d r a w i n g s
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Distribution of elements by
Ridge distribution
Plains distribution
steep ridge:
higher plains
certain characteristics
distribution by slope
Processing units are spread in
distinctive and
minerals or metals, networks
protective feature
and height
neurologic systems, energy
remote area
[slope: 0.00°-30.00°]
is generated and extracted
distribution by heigth
from plants, cooling comes
and characteristics
from atmospheric forces
[height 12.00-120.00m a.s.l.]
(wind, ocean, water) and
[slope 30.00°-90.00°]
an infinite amount of data is
assembling, gathering
stored right in the protein of
computing elements
[height: 0.00-4.00m a.s.l.]
Boxes as an archetypical form
coast direction
and direction
for shelter, storing, accumu-
distribution by heigth
lating
and direction:
e.g. CPUs , capacitors (low
[height: 20.00-104.00m a.s.l.]
temp.)
[southeast winds]
collocation: swarming, gather-
energy transformation
ing, assembling
and accumulation
are assembled by biological
molecules.
and cooling elements
[height: 4.00-12.00m a.s.l.] plant, grow: dna-storing elements lower plains distribution by slope [slope: 0.00°-8.00°] western: farming plots neurologic network energy generation growing veins 0-12m a.s.l. slope 00°-08° bio-neurologic networks cover all over the plains farming plots lower plains substrate atmosphere (protection by ridge) humidity storage plots
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Eva l u a t i o n a n d Di s t r i b u t i o n
mountains
island tower
lower plains
thermal and hydro erosion embankment vs. excavation
western dry side
steep ridge
fall off
geolocical transformations dry / humid hot / cool calm / windy wind erosion biogenic sediment accumulation
eastern wet side high wind forces heavy erosion
lower plains
higher plains
open waters
atmospheric and geolocical forces according to prevalent conditions
plateau
open fields
mountains
mountains
island tower
furrow
western dry side
steep ridge distinctive feature
western dry side
open waters
open waters plateau
plateau
open fields
open fields
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water flow Ffelds (growing veins) serve as supply network for farming plots, shortest path connections
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Se c o n d a r y n e t w o r k
shortest path connections form a communicative neural system integrating machine and environment
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The Unconcious of the machine Concealed in the initial source code of the system there is a gate implemented - possibly by humans that represents the unconscious of the bio-computer. The system doesn´t know about it. The unconscious forces the system to generate elements beyond its own agenda. It is a void core (poetic, irrational, dream-driven), a MacGuffin*- like singular object, that provides shadow from the systems intelligence. *Plot Device, an object, that pushes or disturbs the action. (see: Wikipedia contributors 2020, July 11 )
Maybe it is a reminiscence to a predigital era. This is an enigmatic space in-between. The human trace within the system´s autonomous ecology. Maybe the void core is the system´s initial intention, the reason why the system was developed. The system reinterprets its results, selects parts and implements changes again .
No matter how much data or layers of data are being stored or processed, there is likely the need to pick parts of it in certain moments and arrange them in sceneries, again and again, as the parameters change. This conception sees “world”, digital or analogue, as always to be constructed. Moment stands as well for the state of charge in a computational system. (e.g. infinite number of states in quantum computing) Specific states are to be measured.
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autonomous growing (rather than assembling) surface
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Gr a n u l a r i t y
radically augmenting the number of polygon faces
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stages of growth 1
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Gr o w t h
stages of growth 2-3
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[ D ] A ppl i c a t ion on S it e
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Woodland area and Hydrology
larger area - Tirol region, source map: Land Tirol, tiris
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fig05: Innsbruck, southbound Author: Stephan Sigl information source: Stadtmagistrat Innsbruck
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Si t e a r e a
The city of Innbruck is both an economic centre and
Today, the Alpine region is often portrayed as a largely
an important traffic junction due to its geographical
unspoilt, natural recreational area. In fact, “the Alps
position. Situated in a wide alpine valley crossed by
are neither a natural nor a near-natural landscape,
the river Inn, it is surrounded by very high mountains
but have been profoundly ecologically changed and
and mountain ranges. The city is strongly character-
reshaped by man in the course of its history.”(Baetzing
ized by a dynamic altitude development.
2018 99). Since then, “natural and cultural landscapes have interlocked on a small scale” (Bätzing 2018 10).
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fig06: Innsbruck, cultural and natural landscapes interlocked Author: Stephan Sigl information source: Tirol Atlas, Dep. for Geography, University Innsbruck online: http://tirolatlas.uibk.ac.at [retrieved: 2020, September 04] 51
x
y
Campus Innrain 79682,88 236647,26 Campus CCB 79355,39 236222,78 Campus Sport 77452,88 235843,68 Campus Technik 76399,3 236653,31 Campus Universitätsstraße
80651,64
237331,76
Campus Theologie 80555,86 237198,41 Archiv für Baukunst
80708,01
236346,84
Claudiana 80163,67 237184,85 Fakultät für Bildungswissenschaften
80221,97
236536,81
Forschungsinstitut 80699,81 237956,57 Forschungsschwerpunkt
82604,8 237005,27
Institut für Botanik
79124,52
237100,72
Institut für Erziehungswissenschaften
80620,29
236111,77
Institut für LehrerInnenbildung
77288,38
235957,59
Haus der Musik
80450,24
237229,79
Institut für Psychosoziale Intervention
80699,81
237956,57
Michael-Popp-Forschungsinstitut
80213,24
236117,18
Zentrum für Alte Kulturen
82604,8
237005,27
ULB Aussenmagazin 78948,91 236708,74
coordinates of educational sites and libraries source: Stadtmagistrat Innsbruck
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Academic campus and libraries
closer area Innsbruck, source map: Land Tirol, tiris. educational sites and libraries source: Stadtmagistrat Innsbruck. Projection: MGI Austria GK West (M28)
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D ef ining dis tricts thr oug h shor test p a th a l g o r i t h m
shortest path algorithm starting from libraries and iniversity locations. Stopped by forest borders. shortest path networks not inweaving [any to each] [00] base terrain DEM/DSM model from ogov 5m HF Resample [resolution scale 2, filter scale 1.5] convert HF [triangles, density 1] [01_02_shpth] shortest path analysis convert HF (mesh) [density 0.65; alternating triangles] attribute wrangle-remove points [treshold 0.834; seed 0.478] start group [200618_06_all_edu_locations.dxf] end group: mesh findshortestpath [any to each]
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university (campus) and libraries as knowledge substrate
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Sh o r t e s t p a t h f r o m L i b - Ed u s i t e s
as starting points library and educational site coordinates have been determined as nuclei for a growing algorithm
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Applying eleva ti on ma ni p ul a ti on
manipulating elevation of areas generated by shortest
maximum distance 625, Value 1;
path; borders - hills and valleys emerge
blur method: blur; blur radius: 15]
200623_T7_ctA_01_shpth_areas
HF noise
HF mask by object (shortest path)
HF resample
[input wire from 02_shpth(smooth); wire radius 0.9]
[resolution scale: 1.5, filter: gaussian, filter scale 1.5]
hills and valleys emerge those are transformed by massing tools
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a new topology is generated by manipulating the elevation of areas generated by shortest path end branches
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D isplacement
200623_T7_ctA_02_shpth_areas_distortion HF displacement [control blur radius: 0; substeps: 1 rotate displacement: -90 displace by: vector control layer HF resample [resolution scale: 1.7 filter: gaussian, filter scale 1.5] convert HF [triangles, density 1]
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in a next step these districts are transformed by displacement passes
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E r os ion simulati on
erosion E_01_T7_ctA 200623_T7_ctA_04_E01_f20_d12 freeze 20/80 main [global erosion rate: 1.63] [hydro| erodibility: 1; erosion rate: 0.4; bank angle: 70; spread iterations 48] [thermal | erodibility: 0; erosion rate: 0; bank angle: 35]
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erosion simulations generate more details and a higher resolution
63
catalogue of ter r a i n tr a nsfor ma ti ons
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cat A 5/5 dist. v1
cat B 7/7dist. v1
evaluation catalogue
65
selection f or f u r ther i nv esti g a ti on
66
c a t B 02 d i s t . v3
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In a next step of detailing / zooming in, the source geometry is subdivided in several passes which leads to fragmentation, to a surface growth like - network. Fragmentation is executed by varying scaling of the deviations per division, adjusting amplitude of deviation and selecting the direction of fractalization (either direction of source normal or divergent).
Tests with duplication, triplication and quadruplication of faces were made. Depending on source mesh (from 2.1 to 8.4 million faces) new polygon-meshes with 17 to 35 million faces - as the largest possible number of faces that could have been processed - were generated.
68
Gr a n u l a r i t y , F r a g m e n t a t i o n , Su r f a c e Gr o w t h
fragmentation process
69
subdivision of the source surface assisted by particles and wind force upmost particles moved by wind force form a basis of vertices for a new porous structured surface
70
Windforce - growth from particles
which is treated with the granularity algorithm
71
72
73
structural grid of fragmented surface
74
Implementation of particles
testing of Implementing particles as elements
75
cat B frct 7000m
76
Gr a n u l a r i t y t e s t i n g 7k / 2. 5k
cat B frct 2500m
77
cat B02 frct05 5000m
78
Gr a n u l a r i t y t e s t i n g 5k / 3k
cat B02 frct05 3000m
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Design conception for neural networks and their interface and storage structures on a landscape scale. (1000m)
80
Di s t r i b u t i o n o f e l e m e n t s
Proposal for the purpose of reframing traditional approaches of future knowledge environments.
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85
Archetypical white box devices (operating as black-boxes, pure machines) execute steam-sterilisation-like, well controlled saving and erasing commands.
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Di s t r i b u t i o n a n d Sc a l e
From machinic point of view back to a human scale: larger elements sized 30m-40m and smaller sized 8m-12m
87
The redesigned landscape stands for an aesthetic reflection of a virtual landscape of the mind, which should make knowledge spontaneously and openly accessible, perhaps with the help of augmented reality devices. The connection between man and machine is conceived here by referencing from the address coordinates of a city to the virtual level.
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I n vw e a vi n g h u m a n - n o n - h u m a n
Addresses, in turn, are each a reference to a space where humans can be found. As coordinates, they outlast any structural change, so to speak. A flow of information packets is simulated by a particle flow addressing the network devices and the real-world address coordinates of the city.
coordinates of addresses source data: Land Tirol, tiris. Projection: MGI Austria GK West (M28)
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90
91
92
93
subdividing
transforming fr 030.50
fr 060.20
elevation
res 2.5 filter 1.5
manipulation
any each
interaction
start end
edu/lib locations
fr 010.00
site characteristic t c city ibk lat.47°16'11" long 11°23'39"
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fr 060.40
distribution o
h s
connectivity
fr 020.10
shortest path alg.
x x
subdividing
fr 020.30
shortest path
fragmentation
fr 050.70
hydroerosion simulation
fr 040.80
displacement a distort b by layer
e. hy
referencing fr 080.40
x2 x3
address referencing virtual/real
fr 070.30
height slope
distribution
sc 30-40 sc 08-10
scale experiments
fr 060.90
.r. 1.63 ydr 0.4
granularity
wind force
fragmentation
virtual real
fr 060.70 res 1.3v filter -10
implementation
wind force
particles
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[ E ] S OUR CES
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Bibliography
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Table of figures fig01 Le Répertoire Bibliographique Universel vers 1900 Author: Collections de la Fédération Wallonie-Bruxelles, en dépôt au Mundaneum (Mons, Belgique), Patrick Tombelle https://commons.wikimedia.org/wiki/File:Le_R%C3%A9pertoire_Bibliographique_Universel_vers_1900.jpg [retrieved 2020-08-07] fig02 Voyager Golden Record Author: NASA https://commons.wikimedia.org/wiki/File:The_Sounds_of_Earth_Record_Cover_-_GPN-2000-001978.jpg [retrieved 2020-08-07] fig03 Svalbard Global Seed Vault, Spitsbergen Author: Svalbard Global Seed Vault, Matthias Heyde https://www.flickr.com/photos/landbruks-_og_matdepartementet/15412648967/in/album-72157623004641656 [retrieved 2020-0807] fig04 Chimpanzee seated at typewriter Author: New York Zoological Society https://en.wikipedia.org/wiki/File:Chimpanzee_seated_at_typewriter.jpg [retrieved 2020-08-07] fig05 Innsbruck, southbound Author: Stephan Sigl fig06 Innsbruck, cultural and natural landscapes interlocked Author: Stephan Sigl
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[ F ] APPENDI X
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appendix 01: 3d print prototypes
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appendix 02: T7_B02a_is_20200807_T7_A0a_dgm_dem_5_1000_nodes
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appendix 03: refining resolution
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appendix 04: approaching cartographic tools
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Eidesstattliche Erklärung Ich erkläre hiermit an Eides statt durch meine eigenhändige Unterschrift, dass ich die vorliegende Arbeit selbständig verfasst und keine anderen als die angegebenen Quellen und Hilfsmittel verwendet habe. Alle Stellen, die wörtlich oder inhaltlich den angegebenen Quellen entnommen wurden, sind als solche kenntlich gemacht. Die vorliegende Arbeit wurde bisher in gleicher oder ähnlicher Form noch nicht als Magister/Master-/Diplomarbeit/Dissertation eingereicht.
Datum
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Unterschrift
dedicated to Mother and Father †thank you for your reliable support many thanks to my friends and colleagues and all who have supported me particularly Julia and Mike Wolfgang Teresa, Michela special thanks to Claudia Pasquero, Marco Poletto Maria Kuptsova and Filippo Nassetti for your inspiring, constructive and passionate supervision thanks to you this thesis became an exciting beginning
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What could be more obvious than to conceive of Knowledge Ecology as a landscape, in the open air?
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