ALLEMANDI CONFERENCE PRESS www.allemandi.com Changing the Change Design, Visions, Proposals and Tools Proceedings Edited by Carla Cipolla (Politecnico di Milano), Pier Paolo Peruccio (Politecnico di Torino)
International Conference Thursday 10, Friday 11 and Saturday 12 July 2008 Turin, Italy In the framework of WORLD DESIGN CAPITAL TORINO
2008 | ÂŠ ICSID An Icsid initiative of the IDA
Organizers: Politecnico di Milano and Politecnico di Torino Promoters: CDD - Coordination of Italian Design Research Doctorates CPD - Conference of Italian Design Faculty Deans and Programme Heads Endorsements: ICOGRADA - The International Council of Graphic Design Associations DRS - Design Research Society CUMULUS - Cumulus International Association of Universities and Colleges of Art, Design and Media BEDA - The Bureau of European Design Associations IFI - The International Federation of Interior Architects/ Designers
The publisher is at the disposal of copyright holders of any unidentified picture sources and apologises for any unintentional inaccuracies.
2. Selected papers by theme
Theme 1 Visions / Ways of living T1.1 Scenarios/1
P1. Creative Communities for Sustainable Lifestyles. Visions of sustainable ways of living in Brazil, India, China and Europe... [Penin, Jègou, et. al]
P7. A vision of an urban countryside. Service Design as a contribution to the rururban planning [Meroni, Simeone, et al.]
P13. Beyond Abundance. Motivations and perceived benefits underlying choices for more sustainable lifestyles [Marchand, Walker, et al.]
P19. Projecting new forms of neighbourhoods. The creation of a link between the inhabitants as an answer to changes in society [Lanz]
P14. ARK-INC. An alternative view of what ‘designing for sustainability’ might mean [Singleton, Ardern]
P20. Design Activism as a Tool for Creating New Urban Narratives [Julier]
P2. Design in Public Sector Services. Insights into the Designs of the Time (Dott 07) public design commission projects [Tan] P3. The Melbourne 2032 project. Designvisions as a mechanism for (sustainable) paradigm change. [Ryan] P4. Creative Places for Collaborative Cities. Proposal for the "Progetto Habitat e Cultura" in Milan [Franqueira] P5. Urban Memory Responds to the Change. Improvement and Revitalization of Public Spaces in Macao’s Historical Corridor [Zhu, Pinheiro] P6. “Demolish” and “Construction”. A Research on transition of urban communities and sustainable lifestyle in China [Zhou, Liu]
P8. Other Design at Sulukule. A Local Development Project in a Degenerated Historical Area of Istanbul under the Threat of Demolition [Kaya, Yancatarol, et al.] P9. The Sustainable Development of Traditional Urban Spaces in Wuxi, China -The changing of the road of Zhong Shan (2002-2007) [Li]
P15. Ethically Sound Innovations. The phenomenology and taste of the outdoor elites [Uotila, Rytilahti]
P21. From sustenance to sustainable living in India - Elements of vision based on collaboration with local NGOs. [D’Silva, Jégou]
P22. Knowledge Communities. The actions of design for the P16. Proposals for a Good Life: Senior Thesis construction of Projects from Parsons knowledge-based P10. Beyond localism, looking for sustainability - Product Design 2003-08 territorial systems [Veneziano] [Kirkbride] Designing “typical knowledge” active-action [Lupo] P17. Fashion that helps P23. Eco-Cybernetic P11. Rubbings. Preserving the industrial memories amid change [Zhang, Cao] P12. Landscape Ecology as a basis of Landscape and Urban Planning and Design [Thomas]
us flourish [Fletcher, Grose]
P18. The emergence of shamanic wisdom in the culture of the modern Brazilian project. The perspective of a new rationality for design [Badan]
Theme 2 Visions / Ways of producing T2.1 Models of development/1
T2.2 Models of development/2
T2.3 Production Systems/1
P24. Design for the Majority. Designers (Collaborators) As Enablers Of Social Entrepreneurship And Sustainable Product Development. [Speer]
P29. Designing transition paths for the diffusion of sustainable system innovations - A new potential role for design in transition management? [Vezzoli, Ceschin, et al.]
P35. New Outputs policies and New connections. Reducing waste and adding value to outputs [Ceppa, Campagnaro, et al.]
P41. Crafts_Community_D esign. The strategic role of design to promote local production systems [De Giorgi, Germak]
P30. Design & Transition. What designers can learn from the Transition Movement [Boehnert]
P36. Supporting Communities. Design led collaborations exploring the creative and economic potential of materials made from waste. [Dehn]
P42. Design methodology and sustainability: Between craftwork production and industrial production [Cavalcanti, Andrade, et al.]
P31. Product Design Influencers and Triggers in Micro and Small Enterprises in Kenya. Case Study of Sofa-makers in Gikomba Market, Nairobi. [Osanjo]
P37. MetaCycling. Extending Products' Life Spans Using Virtual Communities and Rapid Prototyping [Lalande, Racine]
P25. Shifting Trajectories. Advancing cosmopolitan localism through participatory innovation [M’Rithaa, Verveckken, et al.] P26. The Influence of Design. Examples from Bangladesh [Bauhoff]
P27. Design culture: from Product to Process. Building a network to develop design P32. Design (x) Diaspora. processes in Latin countries implementing sustainable [Celaschi, De Marco, et al.] development in developing countries [Capjon, Edeholt]
P38. Design for disassembly and reuse for renovation of housing in Flanders. Case Study for existing (high-rise housing) buildings [Paduart, Elsen, et al.]
P43. Textile Traditions and Fashion Design. New Experiential Paths [Conti, Vacca] P44. New Artisanship for New Communities. Frugal Design as the way of the artisan in the new world. [Panghaal]
P45. Exploring indigenous innovations: Ascertaining P28. Technoforest. the Scope for Design P33. Breeding cultures of Designing solutions to exchange. [Lommee] Interventions for their humanly regenerate Successful ecologically disturbed areas [Barbosa] Commercialization [Mehta, P39. Integration of Haptics P34. “Parasitic” Design Punekar] into the Design. A designerStrategies for oriented tool for virtual clay Environmental and Social modelling [Bordegoni, Sustainability - Vision of a Diffuse Universe of Parasitic Cugini] Products and Services [Langella, Dell’Aglio, et al.] P40. A proposal for communicating systemic design. A “systemic tour” showing systems design applications in the region [Signori]
Theme 3 Proposals / Daily life solutions T3.1 Services and places/1
T3.2 Services and places/2
T3.3 Products and technologies/1
P46. The Roots of Change embraced by local food system. Design visions, from the sustainable food system to the prospect multidisciplinary keyprinciples for a sustainable food development [Vasconcelos]
P52. Design for Social Innovation. Enabling replication of promising initiatives for sustainable living in Brussels and Paris [François, Joëlle et al.]
P58. Less Is More: What Design Against Crime Can Contribute To Sustainability. [Gamman, Thorpe]
P65. Macrocomponents. An alternative proposal for the production of home integrated systems. [Cozzo]
P59. Are you worth it? Can you fix it? Investigating the sustainability of mundane activities using theories of everyday practice and human/ object interactions [Fisher, Hielscher]
P66. Rethinking the smart home: An environmental perspective. [Loi, Melican]
P47. Sybaris. Fast good food [Vesseron]
P53. The hidden value of allotment gardens in the urban context and the opportunities for design intervention. [Brault]
Products and technologies/2
P67. A Study on the Framework Development for Context Analysis in Smart Home Environment With emphasis on user’s intention and behaviour. [Ryu, Kim et al.]
P60. Embedding sustainability on do-ityourself products aiming at low-income families. A Case Study on Shelves Used to P68. The sector of Divide Living Spaces. household electrical P55. Contribution of appliances. An integrated Design to EU Projects and [Santos, Lepre et al.] system [Marino] P49. Sustainable mobility Programs in Italy An experience on the use of a P61. Design for all. A codesign in contemporary “design-oriented approach” design experience in rural towns High social and P69. Surrounded by highIndia for healthy indoor in an EQUAL project. technological innovation tech environmental alternative mobility system Compared outputs. [Morra, cooking [Rocchi, Kusume] persuasion. Possibilities for Vitolo] [Marano, Bucchianico] new expressive surfaces [Hipólito, Câmara] P62. Nomadic way of life. Design tools and policies P56. Collaborative P50. Transport in a [Barbosa, Santos] systemic perspective. How Services and Mobile Network. Observation of can we change attitudes and behaviours in people? social innovation and P63. Notes on ecodesign, [Pera] anticipation of sustainable body and the post-human lifestyle in China [Gong, thought. [Rocca] Feng at al.] P51. Service Design to foster premium prize and P64. UFOs - Unidentified P57. Our House: Interior sustainable mobility in Future Objects. A Design and Sustainable urban contexts [Meroni, suggestion on civilization Consumption [Castro] Sangiorgi et al.] brought from creative bottom-up instances [Mendoza]
P48. Designing innovative forms of intermediation and communication. Towards sustainable production and consumption systems [Krucken]
P54. Design tools for sustainable lifestyle: the Italian co-housing experience [Conditi, Ferri]
Theme 4 Proposals / Enabling Systems T4.1 Tourism and mapping
T4.2 Energy and packaging
P70. Social Innovation and Service Design of community-based tourism. The case of Prainha do Canto Verde, in the State of Ceará (Brazil) [Langenbach, Spampinato]
P75. Beyond 1000 Suns. The usage of ‘design culture’ to create a new paradigm for a hybrid heatand-power solar system. [Tarazi]
P80. Design for Social and Environmental Enterprise. Design at the Service of Social Businesses [Brass, Bowden]
P86. DAC_Link. A 2.0 tool for SMEs' design innovation. [Arquilla, Genco]
P71. Design, local development and fair tourism. The EKIT project [Dupont] P72. Knowledge cartographies. Tools for the social structures of knowledge. [Quaggiotto] P73. Handling Changes Through Diagrams. Scale and Grain in the Visual Representation of Complex System. [Ciuccarelli, Ricci et al.] P74. An inconvenient arrow. Visual explanations of ecological cycles in science learning material. [Mølhave]
P76. Energy produced by its own territori. How outputs generate widespread business. [Barbero, Fassio et al.] P77. Design stories for a sustainable society. Case studies of responsibility in practice. [Mottram, Atkinson]
P81. Product service systems and non-market oriented approach. Methodological and ethical considerations from a design perspective [Morelli, Jonas et al.] P82. Design Directory. A strategic web-tool for the Italian design system. [Simonelli, Arquilla et al.]
P83. Conceiving the Design Centre of the future. Transforming the economical and social landscape through multidisciplinary projects and integrated user-centred design research P79. Fish Box in EPS. Zero [Vanderbeeken, Zoels et al.] Impact. [Catania] P84. Systems Design Becomes Easy Like a Game. A travelling exhibition as a tool to communicate sustainable society [Balbo, Corsaro]
P78. The Evolving Role of Design: Opportunities and challenges for the Australian Packaging Industry towards sustainable design. [Avendano]
P87. Research in strategic design: a teaching experience. The design research school model to build a dialog between Brazilian university, society and industry. [Borba, Reyes et al.] P88. The Vision for Mississauga’s City Summit. Collaborating for Change. [Walden] P89. New configurations for networks. The case of the Virtual Institutes. [Bartholo, Bursztyn et al.] P90. An Industrial solution for Kenya and Africa. Using home-grown ideas to create sustainable livelihoods [Amollo] P91. Business Idea Design Supporting tools and services for start-up designoriented companies. [Vignati, Carriera]
P85. Design, Research, Italy. Maps, visions and perspectives of academic design research in Italy. [Bertola, Bianchini et al.]
Theme 5 Tools / Design Theories T5.1 Design education/1
T5.2 Design education/2
P92. A Dialogue on the P98. DEEDS: a new Future of Design Education. Teaching & Learning [Gornick, Grout] resource to help mainstream sustainability into everyday design P93. What if the World teaching and professional Were A More Equitable practice. [Blincoe, FuadPlace Would Any of Us Luke, et al.] (Designers) Be Necessary?[Stairs]
P94. The Experiential Experiment: Is design education sustainable in a changing university environment? [Gaston, Scott] P95. Sustainable Design r&d – Geneva. Bringing University and training design towards Sustainability. [Corminboeuf, Styger]
P96. How you define is how you design. Problematitic definitions in Design for Sustainability Education. [Clune] P97. Looking for Likely Alternatives (LOLA). A didactic tool to approach sustainability by investigating social innovation in daily life. [Thoresen, Jegou, et al.]
P99. The Learning Network on Sustainability. A mechanism for the development and diffusion of system design for sustainability in design schools. [Penin, Vezzoli]
T5.3 Design culture/1
P104. Systems Design Approach. Interdisciplinary/systemic innovation. [Bistagnino]
P110. Sermons in Stones. Argument and artefact for sustainability. [Walker]
P105. Social Design: Exploring the systemic conditions of sustainable change. [Tang, Klein]
P111. Design and values: materializing a new culture. [Malaguti]
P106. Changing the Change: A Fractal Framework for Metadesign. [Wood] P107. Being Here. Attitude, place, and design for sustainability. [Badke, Walker]
P100. Productive friction: a case study of design research between practice, education and community in rural Australia. [Harrisson] P108. 360°Eye on Sustainability. An experimental research P101. Sustainable approach to construct an Product Design: From useful sustainable language. delivering sustainable [Zandanel] products to enabling sustainable lifestyles. [McKay, Raffo, Trowsdale] P109. Non-designed design. A Study on Unprofessional and NonP102. Changing productive Design in Perspectives on Design Shanghai [Chen] Education (…) at the Universidade Federal do Rio de Janeiro (Brasil). [Nicolaiewsky, Monteiro]
P112. Changing a phenomenal change. Reassembling the self through a new ethics of negotiation. [Merwe] P113. Ethics and aesthetics in industrial production: Possible ways for the design in this new century. [Moraes, Figueiredo] P114. Ethics Become Sexy! A critical approach to Design for the right to access to aesthetics and technology in the knowledge society. [Imbesi] P115. A Taxonomy of the Changing World of Design Practice. A vision of the changing role of design in society supported by a taxonomy matrix tool. [Young]
P103. Design-Oriented Futures Wheels. Using Foresight Methodologies in our Design Schools. [Kohtala]
Theme 6 Tools / Design Methods T6.1 Design Thinking/1
T6.2 Design Thinking/2
T6.3 Design Process/1
P116. Designer as Agent of Change. A Vision for Catalyzing Rapid Change. [Banerjee]
P121. Designing Innovation collecting Wishes. A method to integrate individual users into the product innovation process. [Nishiyama, Peruccio]
P127. Design as Activism. P133. Metadesign tools. A Conceptual Tool. [Thorpe] Designing the seeds for shared processes of P128. Integration through change. [Tham, Jones]
P117. Design education as a Change agent: intersections of Need, Learning and Knowledge Transfer Represented in the Designmatters Initiative. [Amatullo]
P122. Design visions, proposals and tools (A Study of Design Methods for Sustainable Innovation). [Quinto]
P118. Everyday P123. When Horns Imagination, Practices, Become Method. Systems. Designing with people for systemic change. [Scaletsky] [Sangiorgi, Drew, Buscher] P119. Visions and possibilities of a transsociation between design and anthropology. A method for a glocally driven product-system innovation. [Staszowski, Leirner]
P124. Is change as good as a holiday? Using metaphysical bonds to design enduring change. [Coxon] P125. Co-Designing a Sustainable Culture of Life. Design tools: designing research methods for sustainable change. [Hocking]
P120. Design and New Horizons of Systemic Interactions. Technology and application innovation for a holistic approach to P126. Hybrid Ontologies. problems. [Vicentini, Bruno] Design knowledge in a hyper-connected fluid society. [Ciastellardi]
communication tools. How design can facilitate social system integration processes. [Scagnetti]
P129. Sustainable Use. Changing consumer behaviour through product design. [Bhamra, Lilley, Tang]
T6.4 Design Process/2
P134. The Slow Design Principles. A new interrogative and reflexive tool for design research and practice. [Strauss, FuadLuke] P135. P-KIT, picture listening for community planning. A simple and effective design research tool for facilitators and habitants in participated urban processes. [Rogel]
P130. The Management of Design as a Tool for Cultural Change Leading to Sustainability. A case study in the Industrial Company of Pernambuco, Brazil. P136. Is design the [Cabral, Cavalcanti, answer to cultural Andrade] acceptability of waterless toilets? A collaborative P131. The Reconstitution approach to design of the Domains of Everyday research. [Fam] Life. A tool for assessing the health of existing conditions P137. Real-time layouting. and a framework for A design â&#x20AC;&#x153;way of doingâ&#x20AC;? to designing sustainable improve participatory solutions based on process tool-kit, applied to principles from the natural the conversion of buildings. world. [Kossoff] [Giunta] P132. Design by Components. An operative methodological tool for the ecocompatible industrial design. [Virano]
P138. Criticality Meets Sustainability Constructing critical practices in design research for sustainability. [Maze]
HANDLING CHANGES THROUGH DIAGRAMS. Scale and Grain in the Visual Representation of Complex System. Paolo Ciuccarelli1, Donato Ricci2, Francesca Valsecchi3
Abstract To change towards a more sustainable development could means to make decisions not only with a systemic approach, but also to be able to decide in the right time: the density. It seems that, when the discipline of Design integrate a systemic approach with the competences of designers in visualization, it can cope with dense situations, providing effective artefacts â&#x20AC;&#x201C; diagrams â&#x20AC;&#x201C; to improve the decision process and making profit from the richness of complexity. The prior findings of the Complexity Science are here assumed as a theoretical framework to have an interpretative model on how the knowledge about systems could be organized and depicted. Three tools to produce effective diagrams, framing, graining and scaling are here discussed though six case studies.
1 Politecnico di Milano (ITALY) - INDACO department. Associate Professor, email@example.com. All the chapters have been produced collaboratively. 2 Politecnico di Milano (ITALY) - INDACO department. Ph.D. Candidate, firstname.lastname@example.org 3 Politecnico di Milano (ITALY) - INDACO department. Ph.D. Candidate, email@example.com
1. Introduction Among the different approaches for sustainability and sustainable development, a common belief seems to arise: the economic, environmental and social dimensions are strongly interlinked. It is necessary to deal with them as a whole (Meppem 2000). This observation, endorsed by the major institutions committed in sustainability development policies (ie. WCED), finds a more general correspondence in the assumption that the world could be seen as networked and as a complex system (Capra 1996; Castells 1996). Over the past forty years complexity theory has become a broad field of study appreciated in a variety of ways and illustrated in books and papers among the others by Nicolis and Prigogine (1989), Anderson, Arrow, and Pines (1988), Jantsch (1980), Holland (1975), Gray and Rizzo (1973), where, older epistemological classifications and domains of expertise have become more permeable (Klein 2004). The increasing regard in system thinking and science of complexity showed - in different ways and times - by economic, environmental and social disciplines (Parker and Stacey 1994; Stacey 2000), and, more germane to our field of study, by planning in social systems (Byrne 1998) and decision-making, seem to reinforce the link between sustainability and Complexity. Byrne (1998) argues that the disclosure of systemic approaches lies in the coherent integration of action and the understanding of phenomena, transcending the limits of analytical traditional modeling techniques. Even if a well-defined “toolbox” for sustainable changes based on the findings of system thinking and complexity science, has not yet been found, there is enough convergence on two pillars that can be used to shape new tools: −
The need for trans-disciplinary sustainable development approach based on a systemic perspective. This statement is supported by the relation established between trans-disciplinary and complexity (Max-Neef 2005);
The interpretation of sustainable development as a learning process. Discussing the integration of the science of complexity, knowledge management and organizational learning disciplines, McElroy (2000) states that “complex systems are, by any other definition, learning organizations”, and adds, on the other side, that “knowledge is the product of natural innovation schemes inherent to all living systems”. If sustainable development means to drive change and to make it happening in complex systems, it has to take part to the learning processes underpinning complex systems behaviors.
It can be argued that sustainable changes need methodologies and tools able to support a learning process in a complex system with a trans-disciplinary approach. Moreover, this learning process should be collective (Manzini, Vezzoli, 1998). Holman says (2007): “Effective, sustainable change are sessions in which people collectively explore each other’s assumptions, seek and expand common ground, shape a desired future, and jointly take ownership of the solutions to the issues at hand”. Furthermore, Clark (1995) argues that traditional development models relating expert knowledge to social need with a top-down approach are increasingly unable to cope with the demands of a complex world. Another point should be considered: time. In the past, changes happened slowly, in different regions at different times. Since 2001, in the “State of the World”, Gardner underlines the global scale and the speed of current changes, emphasizing the need to handle them responsibly and rapidly in order to keep the track of sustainability. The time issue is crucial. Quick reactions and decisions are asked, where, mostly local changes risk to be dampened out if communicated too quickly to the whole system (Prigogine). To stress the importance of time and complexity towards a sustainable perspective, we use the term density: density could be seen as the ratio between time and the amount of data, information and knowledge (interests, point of views…) to be considered in the decision processes that aims to a change. Again, Gardner underlines that, the dramatically fast pace of changes prevent societies from understanding the consequences of
their activities, also because the options for development, in a complex, networked system, have increased in number and complexity. Considering the time constraints, handling changes in a sustainable perspective entails coping with a dense situation, or rather dealing with the complexity of a collaborative learning process that involves all the stakeholders. In the next pages, why and how design should be a discipline integrated in the changing process, in planning and decision-making, will be discussed.
2. Complexity Science and Design discipline One of the most important challenges of complexity science researchers is to facilitate connections among knowledge domains apparently distinct and separated towards themselves, approaching system to be known in a systemic way. This basic idea is confirmed by Gell-Mann (1995), he describes a way about carrying on this approach: “[...] some efforts just getting under way to carry out such a crude study of world problems, including all the relevant aspects, [...]. The object of the study is [...] to identify among the multiple possible future paths for the human race and the rest of the biosphere any reasonably probable ones that could lead to greater sustainability”. This, which seems to be more a challenge than an actual reality, has to recall disciplines by their own nature situated at the edge of different competences domains. Design discipline is one them. There is a need for integrating competencies, labelled by Gell-Mann as “a crude look at the whole”. In this sense, the hypothesis that design may join those disciplines of “looking at whole” outlining a designer profile whose task is to select results from heterogeneous disciplinary fields activating a trans-disciplinary circulation of concepts (Pizzocaro 2000), is made. This means adopting and developing a new attitude based on a theoretical framework that overlaps systems science and complexity theory (Findeli 2001). Designers should use their skills to facilitate the emergence of the system; they should no longer focus on finding solutions to specific problems but on the ability to develop tools that can be self-adaptive, continuously modifiable and improvable (Scagnetti et al. 2007). It has been argued (Friedman 2003; Manzini 2004) that Design has gone through multiple phenomenons that have reshaped its meaning and its nature. Designing within Complexity, in fact, involves both substantive and contextual challenges, from the increasingly ambiguous boundaries between artefact, structure and process to the increasingly large-scale social, economic and industrial frames. This could be seen as the need to cope with a Complex environment in which many projects or products cross the boundaries of different organisations, stakeholder, producer, and user groups. Acting within complexity requires considering the impossibility to reach an exhaustive knowledge of the system in which one operates. It could be passed by developing a strategic stance that allows facing the system changes and evolution. Designer's key competences: see, show, fore-see (Zurlo 2007) could become also key instrument to define strategic changes in a system. More in details the skill of showing could be perceived as the detection and description of all the agents involved and of their relationship. It could be seen, also as the opportunity to visualize complex information referring not solely to the communication of quantitative information but also of intangible values and qualitative data.
3. Communication Design and social Complexity We assume that design interventions could produce changes and transformations both in organizations that start them and in the complex systems in which they are performed. It is possible to state that evolution in organizations, here seen as social complex systems, and complex systems detract themselves from analytic logic rules and could not be leaded with simple actions (Lewin 1999; Lewin, Teresa Parker, and Regine 1998; Olson and Eoyang 2001). Stacey (2000) says that in complex environments the management task is coping with and even using unpredictability, dissents and inconsistency. The tasks of all managers are to deal with 3
instability, irregularity, difference and disorder. We can suggest that coping with unpredictability is a priority even for Design activities. This new approach leads to start questioning (Kurtz and Snowden 2003) the universality of three basic assumptions that had inspired for long time organizational and planning theories: −
Assumption of order – cause and effects in the human behaviour are linear;
Assumption of rational choice – humans facing diverse alternatives will make a “rational” decision maximizing or minimizing some values;
Assumption of intentional capability – the acquisition of a capability implies the use of the capability.
Even if in some contexts these assumptions could be true, new arising situations seem to countervail them, leading to guess that new tools and modes for managing complexity in human systems are required. Even though Complexity Sciences provides new paradigm for mathematical and computational system modelling, it could be also seen as a new approach to the human world. The comprehension of some of complex system structural features (Cilliers 1998) could be useful to outline new modes to act in planning, decision-making, strategy and design. A complex system, is dynamic, involves large number of non-linear interacting agents constrained with the environment. Furthermore, one the most important feature is the unpredictability of the system due to its sensitivity to external conditions. Based on the enlightened features a considerable amount of research projects have been carried on mainly using agent-based modelling to simulate phenomena and evolution of complex systems (Camazine et al. 2001; Weiss 1999), but there are at least three important issues limiting computational modelling application (Kurtz and Snowden 2003; Snowden and Boone 2007): −
Identity – humans bend and deform their identity both individually and collectively;
Rules – nevertheless collective agreements and individual acts are under certain pressure or rules, the matter of intentionality plays a primary role in social complexity patterns (Juarrero 2002);
Local patterns – the high capacity of interacting on large scale throughout abstract concepts on one hand, and, on the other hand, by using technological infrastructures is becoming more and more evident.
This does not mean detracting value to simulation in handling social issues but the use of simulations rather than being used as predictive tools, should be used as supportive ones. Another force differentiating social complex systems from the complex ones could be identified by the fragmentation one and is directly linked to the identity issue. Fragmentation refers to the inhomogeneity (Chapman 2003; Stewart 2001) between social network actors (stakeholders, controllers, influencers, project teams and organizations) involved in system evolution, making effective communication very difficult. Social complexity requires new processes and tools fundamentally attuned to the social and conversational nature of decision making and design work. In this framework a new perspective seems to appear: to enable a more and more valuable interaction level and dialogue among the actors of a social system. It could be useful to shape linguistic tools and competences furthering changes rather than predicting and leading them. Focusing this new perspective on that side of Design discipline dealing with languages, the Communication Design could face the creation of visual languages affording representations of Complex systems, easing the spotting of awkward, creating shared visions within multi-actor contexts. The challenge lays on the use of communication artefacts utilized for the definition of common objectives in a project to create pivots so as to work in a resourceful manner. To act in such kind of domains, increasing the interaction and communication level becomes a fundamental action in order to manage and handle changes. Diagramming and mapping, typical communication design artefacts, could facilitate to face the proposed challenge (Abrams and Hall 2006). Diagrams as devices for shared strategies and 4
evaluation of projects impact have an enormous potential to improve decision making processes thanks to their ability to involve all the actors, overcoming the possible hurdles created by specialized knowledge and languages. This definition of diagram includes all those artefacts (maps, scenarios, charts, storyboards, etc.) featured by a revealing capacity, a diagrammatic attitude finalized to the act of design (Scagnetti et al. 2007). Diagrams from this viewpoint could help designer to shape clearly complex problems, they are media between what is known about a system, and what it is; they could display not only quantitative data but also ideas, concepts, frames, schemes, viewpoints, perspectives and values of the system observer. To sum up, extending and dropping some theoretical speculation about diagram reflections developed in architecture field of study (van Berkel and Bos 1998), four diagrams characteristics (Corbellini 2007), could be enlightened: −
Condensation – diagrams and the realm of tangible designed world, are related by their capacity to cope with the elaboration of huge amount of data and variables;
Bridging – diagram could express relation between polychrome information often non homogeneous, suggesting unexpected description of phenomena;
Proliferation – diagrams as dialogue enabler could generate diverse ways of thinking about problems being faced, becoming, also, story-telling devices;
An- exactitude - The creation of a diagram is a partial and never exhaustive description of the environment. It is a narration in which inevitably a choice of what will be represented is made: it is a political stance, intentionally structured and thus arbitrary.
This feature shows the principle of responsibility designers should be aware of.
4. Designing diagram to design In order to produce effective diagrams some preliminary operations have to be performed about information gathering and transformation. To design diagrams, information and data must be collected from different disciplines, with the aim of collecting not only an extensive knowledge about a Complex System, but also to synthesize its regularity (or irregularity) (Scagnetti et al. 2007) in a goal-oriented way, producing new knowledge about the system in which intervene. Beyond diagrams differences in visualization and information management modes, they seem to be comparable in the way they treat information, or, to be more exact, in the way they allow us to treat information. This common feature might be an interesting approach for an effective modality to design them and to study how they are related to the described system. Assuming information as a key element to start visualizing complexity, it could be also seen as a parameter to “measure4 complexity”. An interesting way to quantify complexity is the length of a message to describe a certain feature of a system. It referring to a description could be nothing but a subjective property. Complexity, however defined, is not entirely an intrinsic property of the described entity; it also depends to some extent on whom or what is doing the description. The observer and the system are in a relationship. As a more general definition (Bar-Yam 1997) we could present that an observer is a social complex system, which through interactions retains a representation of another system (the observed system) within itself (Pizzocaro 2004). Obviously 4 The number of ways of measuring complexity has grown fast. This multiplication of measures has been taken by some to indicate confusion in the field of complex systems. In fact, the many measures of complexity represent variations on a few underlying themes. Here is an list of measures groups: 1. Difficulty of description. 2. Difficulty of creation. 3. Degree of organization: a) Effective Complexity. Difficulty of describing organizational structure, whether corporate, chemical, cellular, etc. b) Mutual Information. Amount of information shared between the parts of a system as the result of this organizational structure.
necessary condition to adopt this measure is to adopt a language intelligible to the actors involved in the representation of the complex system. Gell-Mann (1995), introducing this concept, says: “The length of the shortest message that will describe a system [...] employing language, knowledge, and understanding that parties share”. This leads us to the consequence that defining complexity request to define and share, among other parameters, the thickness and extension adopted in describing the system. Furthermore, considering diagrams as picture shaping representation of complex systems, in order to design them it is required to provide conceptual and operative tools able to care and share these parameters. Using these tools increase designer consciousness in his condensation operations. In this framework, we have defined project team and at the same time multi-actors organization, involved in handling changes in complex system, as the observer of the same system. Obviously, multi-actors organisations are here assumed as social complex system. The presented tools, which will be discussed throughout the paper are to be considered as a deepening of previous presented results during the international conference IASDR07. They refer to the first two steps: analysing e representing, belonging to a wider a methodology (Scagnetti et al. 2007). The aim of this paper is defining three fundamental tools in generating diagrams, which define their features: −
Framing – the definition of the complex system extension domain being enquired and in which intervene;
Graining – the definition of the threshold accuracy and deepness of the information whole, helpful to describe the system;
Scaling – the definition of the viewpoint on the represented domain and related visualization.
The first two tools address knowledge objectives, whilst the third one dealt with communicative goals.
4.1. Framing. The representation of a Complex system presents several difficulties arising from its structural features. In order to achieve an interpretative model on how the knowledge about systems could be organized and depicted is appropriate to define a key concept: Complex systems are usually open and interact with the environment they live in. This concept implies that it is difficult to clearly define the space where information should be gathered; therefore, it could be useful to define how wide the description will be, subsequently the system visualization, creating a frame. In design interventions frames are needed to narrow the number of information to make the system manageable and describable. It is important to notate it is more helpful to use the term frame rather than the word boundary. Boundary recalls a piece of land within a fixed limit, a frontier, and originally referred to the word bound meaning limits imposed or under obligation, and consequently could suggest something that inhibits actions. It has been argued that (Kurtz and Snowden 2003): “the boundaries we consider are more like phase changes than physical boundaries (though they could be physical boundaries, if those boundaries coincide with phase changes)” On the base of this assumption, even if the space where a complex social system acts could be identified on a geographical or territorial base, a more faded term is required: frame could be this term. The etymology of the word frame5 comes from the Greek KORONIS “something blended or curved” (Pianigiani 1990), so a process of framing could be described as a process of looking where the things start changing or blending in an environment that is obviously seamless. 5 We refer to the Italian term cornice.
A good framing action might be based on the system behaviour perception. In other words it answers to the question: Where do we expect starting patterns of interactions change? Any frame is identified by who is attempting to describe the system for a particular purpose and therefore affected by biases, interests and vision. Cilliers (1998) explains this concept through the interrelation of the framing process to the position of the observer of the system. Moreover, framing is to be related to the temporal dimension of the system, not only they evolve through time, but past events are co-responsible of present behaviour. Ignoring the time dimension could produce inaccurate representations, synchronic snapshot of diachronic processes. Such kind of action is a very delicate one. There is a need to communicate and share how the framing process has been performed in order to discuss and to create consensus among all the actors involved in a specific design process. The action of framing ensures the system is defined in both relevant and manageable way, working on the domain extension field is wanted to be known.
4.2. Graining In order to manage the description of the system, what information accuracy will be considered, have to be also decided. To set a resolution level, defining the systems structure, could be useful to arrange a process of graining. To grain information is a fundamental action considering the amount of sensible data much greater than the available, perceptible and intelligible one. Even if we assume the possibility of obtaining all the information about a complex system it will be almost impossible to use it, since it creates a situation of information overload6. Furthermore, analysing a complex system implies the acquisition also of noisy and incomplete data. Their huge amount, its noisiness and incompleteness if associated to a lack of selected and monitored data, constraints the system describer to a cumbersome filtering and sieving procedure. The building of tools able to effectively parse data is required. Graining is the properly tool for doing that. It operates by making approximations, by ignoring details on finer scales, creating grained observation of the system at a resolution that shows the overall pattern of the system and the pattern of the elements in it. It is a crucial process for highlighting the regularities immersed in the observed system7. Adopting graining as conceptual tool, however able to transform the way we look and act in complex systems, it is possible to set two end points of a continuum where the various way where grained observations could fit in. On one hand are fine-grained observations, a near sighted way to perceive rendering detailed impressions, on the other hand coarse-grained observation, a far sighted observation rendering rough impressions. In other terms, if we make a coarse observation, the system describer can consider only large cluster of agents in the systems (i.e. institutions) obviously a lot of smaller detail will get lost in this process. On the contrary, a fine system examining, in microscopic details, the system observer has to keep track of each agent and of all patterns. Looking for regularities could be obscured “by the buzzing activity at lower level”8 (Cilliers 1998). Grain is a quite complicated concept, and requires more than a metaphor to clearly depict how it works. In addition, another example could be given (Gell-Mann 1995): envisioning taking a whole picture of a complex system in order to spot on a very small detail, the observer should zoom a lot the picture. Reaching a certain level he will only see the single grain of the picture film 6 The term was used by Toffler in 1970 and is often used to describe the simple notion of receiving too much information. It has led to various synonyms and related terms as for example cognitive overload, sensory overload , communication overload, knowledge overload, or information fatigue syndrome. 7 It is useful to remind that Complexity science mostly asks: What causes order and regularities? (Mainzer 1996) . 8 A useful example is given by Chris Stephens: consider the number of degrees of freedom of the atoms composing a solid object (like a pen). This is enormous (≈ 1022). However, in order to describe the motion of a solid object, we just need 6 degrees of freedom. We have then a very much reduced “coarse-grained” description in terms of many fewer variables. So, we need to understand how more appropriate effective degrees of freedom, such as the translational and rotational ones of the rigid body, emerge and offer a more appropriate description of the dynamics. Of course, the coarse-grained description is not exact. How the resultant loss in precision affects the description depends on what one wants to know about the system.
and instead of distinguish the desired object, he will only perceive a group of stains. From this example follows that grain is a sort of threshold operator acting on the data gathering deepness. The process of graining narrows the amount of data should be managed by a representation, and then by a diagram. This means valuing the complexity of a system based on its description is function only of its resolution: the grain. From a philosophical point of view should be asked that graining introduces an element of subjectivity into the theory. Furthermore, could be objected that the grain threshold is not decided upon unambiguous and rational choices but rather by the describer. As a general rule common sense should be used to distinguish between observable and unobservable quantities, manageable and unmanageable. As the coarse graining is subjective, so measurements are inherently subjective operations (Bais and Farmer 2007). Graining helps in addressing the following question: At what deepness is it expected to find regularities or irregularities? Even if the term grain finds its roots in the photographic vocabulary and the Complexity Science uses it to explain some of its operations, in this framework it has to be considered as an effective parameter to be shared in reaching a common representation of the analysed space. Operatively, grain threshold process should be performed both on agents and on data about them. Information on complex system should be distinguished in flows (i.e. tangibles: goods or money; intangibles: information) and environmental ones (proximity, closeness, influence).
4.3. Notes on the adoption of framing and graining tools The main idea is that the representation of a complex system is necessarily linked to the purpose of the representation itself and the disclosure of the purpose is a necessary condition of the same process. In other words one of the capabilities of complex system is to be able to acquire, compare, and store information concerning the environment for future use. Furthermore this process is related to the meaning conferred to the data and information in order to produce knowledge of the studied system. Meaning in this term could be seen as the result of a dialectical process. The aim and the meaning have to be made explicit in order to achieve a successful representation, and consequently a good visualization. The framing action as well the grain threshold level should be tuned on the purpose and the questioning wills about the system in which intervenes, avoiding senseless and uneconomical processes. For instance to trace an economic system is useless to know all about the movements of every penny or Euros even if all the economic system is a pattern of movements of penny or Euros clusters. The cost to trace every agents, data, information or relationship is higher than the profit it could generate, the cost should be seen here as a function of two main parameters: −
time and resources for data gathering;
time and capacity for data processing.
In other words it is a function of the density. A shared use, among design team, of framing, graining tools is necessary to avoid some difficulties of representation processes (Burkhard 2004; 2005): −
Information overload – Actors cannot identify the relevant information;
Information misinterpretation – Actors cannot understand, evaluate and interpret the information;
Information misuse – Actors cannot use or misuse the information.
Involving actors since early phases of representation and then visualizations helps to go over the different backgrounds (different ways to understand and interpret visualizations), and provide relevant information for design interventions.
Even if the two processes of framing and graining are not reversible, and exclude a part of the system to be understood and represented it has been stated that “harnessing complexity involves acting sensibly without fully knowing how the world works” (Axelrod and Cohen 1999). But design is a discipline that for its own nature has to cope with (Buchanan 1992; Cross 2001) open, ill-defined or wicked-problems (Conklin 2003; Rittel and Webber 1973), that happen in complex social systems. Moreover, what the system is depends on what is asked about it: different stakeholders have different views about what the system is and what constitutes an acceptable way to intervene in it – the problem. Since open problems have no stopping rule ending when “good enough” solution is reached (Simon 1996), it is also useful to say that even the framing action and the graining process could end only when it is found a good enough resolution satisfying all the actors involved in the system representation or in the design intervention.
4.4. Scaling Operative instructions able to visualize phenomena could be mutated from a cartographic approach. Among the various tools provided by cartographic repertory, scale is a very useful tool in managing also visualization of Complex Systems. It chooses the scene and the viewpoint to be visualized. The scaling process does not affect the representation of the system, information gathered will be still available even thou they will not be depicted: like a movie-camera, trough the scale level setting only a part of a known reality is shown. Far from being only a zoom of the map, it represents a fundamental step to depict information. The setting of the scale level consists in an operation that aligns the distance from the observed systems to the communicative goals pursued, as determined by the observer cognitive and perceptive capacity. Scale do not provide parameter to define how have to be know a system, instead it define how a system will be communicated; scale does not require an object to be know but a several object to be depicted. Cartographic scale is becoming “visualization” scale (Montello 2001). The concept of scale is often confusing, even in the cartographic field of study having multiple referents: −
Cartographic scale – the object depicted size relative to its actual size in the world;
Analysis scale – the size at which some problem is analysed9;
Phenomena scale – the size at object or processes exist, regardless of how they are studied or represented.
Although the three meanings are interrelated10, we mostly refer to the first meaning. Scale setting level have enormous consequence for the degree to which information is generalized. Generalization refers to the amount of details included in a visual representation, in this term scale imply processes of simplification, selection and enhancement of some particularly interesting features in order to accomplish a communicative goal (Lam and Quattrochi 1992). It is useful to remarks that choosing appropriate scale level, again, can only be decided in empirical way. Starting by the same complex system, scale allows to explore in details system elements, or to read the overall characteristics on the base of communicative needs.
9 Analysis scale present some analogies with the graining tools, in fact terms such as resolution or granularity are often used as synonyms for analysis scale. 10 Choosing the map scale depends both on the scale at which measurement are made and on the scale at which an object of interest exists.
5. Case Studies An empirical verification about the use and the application of the proposed tools has been performed in a didactic laboratory, the Density Design Lab11. Established in September 2004, the lab has been conceived as a platform for verifying the potential of communication artefacts in helping decision making. The course lasts six months, and usually forty students compose the class. Students are introduced to the concept of diagrams to support decision making processes. They generally work in groups of 6/8 members. To each group is assigned a system to work with and to verify the effective complexity. The whole group manage the data collection as well as the problem setting phase, under the supervision of an external advisor12. We choose topic coherently to students interests trying to explore relevant socio-political issues. In the last edition students explored: −
the Italian cinematographic system;
the fashion system;
the contemporary art system;
the hospital - patient system;
the Italian transportation infrastructure system;
the Italian media landscape system.
The excepted output of the analysis and representation phase is a diagram able to identify some possible evolutions of the system student coping with, and a communication strategy to activate the evolution, the whole design experience is reported on the blog13. Even if we try to afford a fully understanding of the system and a relevant data gathering, the laboratory cannot provide a real decision making process albeit the decision table is simulate and the real actors often involved.
5.1. Frame setting discussion All the six studied system were represented by real data, only the hospital system was represented abstracting it, creating an ideal model. In this case the framing has been set to the physical bound of the ideal hospital. Framing seems to be reasonably well defined, attuned to the purpose of the system description, namely to understand the relationship between the hospital structure and the patient emotions. In general, framing process has been determined by spatial limits: national extension for cinematographic, media and infrastructure ones, international framing for the fashion system. Some consideration emerged about not appropriate framing choose: in cinematographic systems, the frame should be extended not only to the production chain (producers, distribution and directors of film) but considering hidden actors also, like political influence and religious interferences. It has to be admitted, the difficulty to grasp such kind of information hindered the possibility to consider, and then visualize, relevant connections within system. So the framing resulted too tight considering the initial cognitive objective: to discover how the financing process in the system is performed. Contemporary art system suffered a similar situation: referring the representation only to the Italian territory without considering the international echo connected to their scope, it was almost impossible to pursue the intent to trace contemporary art market dynamic. 11 Density Design Lab is a research and experimental laboratory, born as a laboratory course in the final year of the Master Degree Course in Communication Design at the Politecnico di Milano. 12 The advisor is an expert of the system to be known and his task is to advise the group supporting them in the system exploration. 13 A fully detailed (pics, images, stories, knowledge base) description and explorations of the project is available at <http://densitydesign.org>
The fashion system case introduced time variable into framing process, limiting the representation to the last 5 years, which can be consider a relevant period in the fashion system evolution. In the infrastructure system the frame seems to be well defined, focusing on the Italian controversies which new infrastructures planning and implementation create at local level. Students considered also the correlation between European laws and normative regulating the infrastructural network development. Purpose
Italian cinematographic system
Are the financings managed or influenced by subjects whose individual affairs are in conflict with the role that they dress again inside the system?
National extension, only focussed on production chain
Fine: single director and movie
Do fashion capitals still make sense? Moreover are there new actors on the international scene?
Worldwide, 5 years
Coarse but â&#x20AC;&#x153;deformedâ&#x20AC;?
Contemporary art system
Which are the relations between influencers and the valorisation mechanism?
Which is the relationship between the hospital structure and the patient emotions
Physical bound of the hospital
Very coarse: groups, hierarchies, protocols of the structure
Attuned to the communicative goals.
Italian media landscape
Are users reached only by few editorial groups? Is the same content provided in different ways giving a wrong idea of pluralism?
Fine: Editorial products
Italian transportation infrastructure system
Which is the dynamic leading to controversies developing new infrastructures?
National extension, EU extension for laws and normative
Medium: Groups and institution, impact, % of project progress, cost
Some cluster of information were been depicted much in details than needed
Tab. 1 Resume of the system representation and visualization purpose and frame, grain setting parameters
Img. 1. The Italian transportation infrastructure system diagram and some close up
5.2. Grain setting discussion Not attuned to the purpose frames, easily affect graining process too, as it happened in the case of cinematographic system. Focusing on the production chain, fine grained filter has been applied detailing all the single film and director. The result is a huge quantity of single data not related each other; a coarser graining description of the system, investigating aggregations instead of single elements could better give sense to the influences affecting the production chain. The approach to graining process has been different: sometimes very coarse (hospital system), sometime fine (contemporary art system). In other cases a middle level has been chosen: in infrastructure system grain, as in the fashion one, referring only to institutional agents and aggregate data. It has to be said, in the fashion system, due to unavailability of data the graining level has been â&#x20AC;&#x153;deformedâ&#x20AC;?. Infrastructure system group sets the grain threshold starting by associations and local groups to ministries, departments and govern. Furthermore, in order to have a controllable parameter they selected data about infrastructure project on the base of project impact accounting the number of people involved, percentage of project progress and cost. Often the relationship between framing and graining is very close as the case of the hospital system. The need to understand how an hospital works and which is the role of the patient, as stated in the investigation hypothesis, a very coarse level of grain has been required: representation concerned only the dynamics between different hierarchies and protocols of the structure. A finer graining level would have compromised the disclosure of the purpose, to understand the general mechanism of the hospital, and to trace every single individual agents would have masked the overall dynamic of the system.
Img. 2. The hospital system diagram and some close up
5.3. Scale setting discussion In the six complex systems analysed the difficulties in choosing the degree of generalization of information, related to a specific communication goal, has been also faced. It could be observed a general bias to visualize the system as it was known, too much details, not aligning the distance from the observed systems to the communicative goals pursued. Is the case of cinematographic system in which is not provided any kind of scaling, so the diagram do not shows the overall characteristics of the system itself. Instead, in the case of Hospital, scaling was coherently applied, and aligned. The diagram of the system describes the structure as well as the dynamics of the relations among the various agents constituting it. Furthermore to underline some of information has not been aggregate to clearly shown some of the analysis phase findings. In the case of Transportation system in which framing and graining were well defined, some cluster of information were been depicted much in details than needed.
6. Conclusion The tools described in this paper suggest paying a special attention to improve designer awareness in the use of diagrams; their use is proposed providing a theoretical framework. To sum up: the tools requires those who have to cope with complex issues to understand what is the purpose of system representation as well to stimulate a shared vision of it even through the use of framing, graining and scaling processes. The framework proposed has been refined trough 4 years of didactic activities, leading to some limits, both logistic and related to the availability of only secondary resources. Thereby in the case studies, the use of time as a framing parameter has been affected by the lack of a real decision- making table and it has not been properly explored. Overall, the experiments enlightened the effectiveness of the proposed tools, providing the students whit clear reference to approach complex systems. The processes proposed, negotiated with the teaching body and the experts, and emphasized the need of a recursive definition in order to share it. It has to be admitted that in some case the expected data availability affected too much the use of the tools, influencing both the effectiveness and the awareness in their use, they are the case in which parameters seems to be not tuned to the purpose of system enquiry. The next step of this ongoing research would be a testing phase extended also to non academic contexts14. Some difficulties have to be noticed in the communication of the parameters setting to external actors to whom visualization have been presented, but in general term the diagrams effectiveness as facilitation tool has been well valued. Furthermore, it could be useful to design proper system to label visualization, developing new kind of legend. Information about how the framing, graining and scaling process have been performed, should be taken into account in this new kind of notation, in order to provide a clear explanation to all those who have to work with diagrams to help changes happen.
14 The tools and the processes here described will be adopted, in the Summer schools Workshop in the framework of Turin World Design Capital 2008. Further detail are available here: <http://www.torinoworlddesigncapital.it/portale/en/content_2.php?sezioneID=288&ID=437&categoriaID=382>
References Abrams, Jant, and Peter Hall, eds. 2006. Else/where: mapping new cartographies of networks and territories. Ed. Jant Abrams and Peter Hall. Minneapolis: University of Minnesota Design Institute. Anderson, Philip W., Kennet Joseph Arrow, and David Pines. 1988. The Economy as an Evolving Complex System. Proceedings of the Santa Fe Institute. Redwood City: Addison-Wesley. Axelrod, Robert, and Michael D. Cohen. 1999. Harnessing Complexity: Organizational Implications of a Scientific Frontier. New York: Free Press. Bais, F. A., and J. D. Farmer. 2007. The Physics of Information. In Handbook of the Philosophy of Information, ed. P. Adriaans and J. van Benthem. Amsterdam: Elsevier. Bar-Yam, Yaneer. 1997. Dynamics of complex systems. Cambridge: Perseus. van Berkel, Ben , and Caroline Bos, eds. 1998. Diagram Work: Data Mechanics for a Topological Age. In ANY Acrchitecute New York, ed. Ben van Berkel and Caroline Bos. 23. New York: Anycorp. Buchanan, R. 1992. Wicked problems in design thinking. Design Issues 8, no. 2: 5-21. Burkhard, Remo A. 2004. Visual Knowledge Transfer between Planners and Business Decision Makers. In Developments in Design & Decision Support Systems in Architecture and Urban Planning, Eindhoven, Eindhoven University of Technology, ed. Jos P. van Leeuwen and Harry J. P. Timmermans, 193:193-208. Eindhoven: Eindhoven University of Technology. ---. 2005. Towards a Framework and a Model for Knowledge Visualization: Synergies Between Information and Knowledge Visualization. In Knowledge and Information Visualization, 238-255. http://dx.doi.org/10.1007/11510154_13. Byrne, David. 1998. Complexity theory in the social sciences. London: Routledge. Camazine, Scott, Nigel R. Franks, James Sneyd, et al. 2001. Self-Organization in Biological Systems. Princeton University Press. Capra, Fritjof. 1996. The web of life : a new scientific understanding of living systems. 1st ed. New York: Anchor Books. Castells, Manuel. 1996. The rise of the network society. Malden Mass.: Blackwell Publishers. Chapman, R. 2003. Archaeologies of Complexity. London: Routledge. Cilliers, Paul. 1998. Complexity and Postmodernism: Understanding Complex Systems. London: Routledge. Conklin, J. 2003. Wicked Problems and Social Complexity. Dialogue Mapping: Defragmenting Projects through Shared Understanding. Forthcoming. CogNexus Institute. Corbellini, Giovanni. 2007. Ex libris : 16 parole chiave dell'architettura contemporanea. Architettura arte paesaggio, 2. Milano: 22 Pub. Cross, Nigel. 2001. Designerly Ways of Knowing: Design Discipline versus Design Science. Design Issues 17, no. 3 (Summer): 49-55. Findeli, A. 2001. Rethinking Design Education for the 21st Century: Theoretical, Methodological, and Ethical Discussion. Design Issues 17, no. 1. Friedman, Ken. 2003. Theory construction in design research: criteria: approaches, and methods. Design Studies 24, no. 6 (November): 507-522. doi:10.1016/S0142-694X(03)00039-5. Gell-Mann, Murray. 1995. The Quark and the Jaguar: Adventures in the Simple and the Complex. New York: Owl Books. Gray, William, and Nicholas D. Rizzo. 1973. Unity Through Diversity . New York: Gordon & Breach. Holland, Jonh H. 1975. Adaptation in natural and artificial systems. Ann Arbour: University of Michigan press. Holman, Peggy, Tom Devane, and Steven Cady. 2007. The Change Handbook: The Definitive Resource on Today's Best Methods for Engaging Whole Systems. 2nd ed. Berrett-Koehler Publishers, January 4. Jantsch, Erich. 1980. The Self-Organizing Universe, Oxford. Oxford: Pergamon Press. Juarrero, Alicia. 2002. Dynamics in Action: Intentional Behavior as a Complex System. Cambridge: MIT Press. Klein, Julie T. 2004. Interdisciplinarity and complexity: An evolving relationship. E: CO 6, no. 1-2: 2-10. Kurtz, C. F., and D. J. Snowden. 2003. The new dynamics of strategy: Sense-making in a complex and complicated world. IBM Systems Journal 42, no. 3: 462-483. 16
Lam, Nina S. N., and Dale A. Quattrochi. 1992. On the issues of scale, resolution, and fractal analysis in the mapping sciences. The Professional Geographer 44, no. 1 (February): 88-98. doi:10.1111/j.0033-0124.1992.00088.x. Lewin, Roger. 1999. Complexity: Life at the Edge of Chaos. University of ChicagoPress. Lewin, Roger, Teresa Parker, and Birute Regine. 1998. Complexity theory and the organization: beyond the metaphor. Complex. 3, no. 4: 36-40. Mainzer, Klaus. 1996. Thinking in Complexity: The Complex Dynamics of Matter, Mind, and Mankind. New York: Springer-Verlag. Manzini, Ezio. 2004. Il design in un mondo fluido. In Design Multiverso: Appunti di fenomenologia del, ed. Paola Bertola and Ezio Manzini. Milano: Edizioni Poli.Design. Max-Neef, Manfred A. 2005. Foundations of transdisciplinarity. Ecological Economics 53, no. 1 (April 1): 5-16. doi:10.1016/j.ecolecon.2005.01.014. McElroy, Mark W. 2000. Integrating complexity theory, knowledge management and organizational learning. Journal of Knowledge Management 4, no. 3: 195 - 203. doi:10.1108/13673270010377652. Meppem, Tony. 2000. The discursive community: evolving institutional structures for planning sustainability. Ecological Economics 34, no. 1 (July): 47-61. doi:10.1016/S0921-8009(00)00151-8. Montello, Daniel R. 2001. Scale in Geography. International Encyclopedia of the Social & Behavioral Sciences. doi:10.1016/B0-08-043076-7/02473-6. http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B7MRM4MT09VJ34G&_rdoc=9&_hierId=151000187&_refWorkId=21&_explode=151000186,151000187&_fmt=high&_orig=na&_doc anchor=&_idxType=SC&view=c&_ct=15&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=869e a92f14c3b1d57e69c2a2d0e9696e. Nicolis, Gregoire, and Ilya Prigogine. 1989. Exploring Complexity: An Introduction. In . New York: Freeman. Olson, Edwin E., and Glenda H. Eoyang. 2001. Facilitating organization change. San Francisco: Jossey-Bass / Pfeiffer. Parker, David, and Ralph Stacey. 1994. Chaos, Management & Economics: The Implications of Non-Linear Thinking. Coronet Books, April. Pianigiani, Ottolino. 1990. Cornice. In Vocabolario etimologico. La Spezia: Fratelli Melita. Pizzocaro, Silvia. 2000. Complexity, uncertainty, adptability: Reflections around design research. In Doctoral education in design: Foundations for the future, ed. David Durling and Ken Friedman. London: Staffordshire University Press. ---. 2004. Design e complessitĂ . In Design Multiverso: Appunti di fenomenologia del, ed. Paola Bertola and Ezio Manzini. Milano: Edizioni Poli.Design. Rittel, Horst W. J., and Melvin M. Webber. 1973. Dilemmas in a general theory of planning. Policy Sciences 4, no. 2 (June 1): 155-169. doi:10.1007/BF01405730. Scagnetti, Gaia, Donato Ricci, Giovanni Baule, and Paolo Ciuccarelli. 2007. Reshaping communication design tools. Complex systems structural features for design tools. In . Hong Kong: Sharon Poggenpohl, November 12. http://www.sd.polyu.edu.hk/iasdr/proceeding/papers/Reshaping%20tools.%20Complex%20Systems%20structural %20features%20for%20design%20tools.pdf. Simon, Herbert A. 1996. The sciences of the artificial (3rd ed.). Cambridge: MIT Press. Snowden, David J., and Mary E. Boone. 2007. A leader's framework for decision making. A leader's framework for decision making. Harvard business review 85, no. 11 (November). Stacey, Ralph. 2000. Complexity and Management: Fad or Radical Challenge? 1st ed. Routledge, November 7. Stacey, Ralph D., Douglas Griffin, and Patricia Shaw. 2000. Complexity and Management: Fad Or Radical Challenge to Systems Thinking? London: Routledge. Stewart, Peter. 2001. Complexity Theories, Social Theory, and the Question of Social Complexity. Philosophy of the Social Sciences 31, no. 3 (Settembre 1): 323-360. doi:ER - . Weiss, Gerhard, ed. 1999. Multiagent systems: a modern approach to distributed artificial intelligence. Ed. Gerhard Weiss. MIT Press. Zurlo, Francesco. 2007. Design Strategico. Milano: Edizioni Poli.Design.