02b Dossier Appendix Handling Changes Through Diagrams

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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 notonly with a systemic approach, but also to be able to decide in the right time: the density. Itseems 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 –diagrams – 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 anddepicted. Three tools to produce effective diagrams, framing, graining and scaling are herediscussed though six case studies.

1 Politecnico di Milano (ITALY) - INDACO department. Associate Professor, [email protected]. All the chapters have beenproduced collaboratively.2 Politecnico di Milano (ITALY) - INDACO department. Ph.D. Candidate, [email protected] Politecnico di Milano (ITALY) - INDACO department. Ph.D. Candidate, [email protected]

mailto:[email protected]






1. Introduction

Among the different approaches for sustainability and sustainable development, a common

belief seems to arise: the economic, environmental and social dimensions are stronglyinterlinked. 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 asnetworked and as a complex system (Capra 1996; Castells 1996). Over the past forty yearscomplexity theory has become a broad field of study appreciated in a variety of ways andillustrated 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 (Klein2004). The increasing regard in system thinking and science of complexity showed - in differentways 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 (Byrne1998) and decision-making, seem to reinforce the link between sustainability and Complexity.

Byrne (1998) argues that the disclosure of systemic approaches lies in the coherentintegration of action and the understanding of phenomena, transcending the limits of analyticaltraditional modeling techniques. Even if a well-defined “toolbox” for sustainable changes basedon the findings of system thinking and complexity science, has not yet been found, there isenough 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 betweentrans-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 andorganizational 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 livingsystems”. If sustainable development means to drive change and to make ithappening in complex systems, it has to take part to the learning processesunderpinning complex systems behaviors.

It can be argued that sustainable changes need methodologies and tools able to support alearning process in a complex system with a trans-disciplinary approach. Moreover, this learningprocess 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 thesolutions to the issues at hand” . Furthermore, Clark (1995) argues that traditional developmentmodels relating expert knowledge to social need with a top-down approach are increasinglyunable to cope with the demands of a complex world.

Another point should be considered: time. In the past, changes happened slowly, in differentregions at different times. Since 2001, in the “State of the World”, Gardner underlines the globalscale and the speed of current changes, emphasizing the need to handle them responsibly andrapidly in order to keep the track of sustainability. The time issue is crucial. Quick reactions anddecisions are asked, where, mostly local changes risk to be dampened out if communicated tooquickly to the whole system (Prigogine). To stress the importance of time and complexity towardsa 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 beconsidered in the decision processes that aims to a change. Again, Gardner underlines that, thedramatically fast pace of changes prevent societies from understanding the consequences of

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their activities, also because the options for development, in a complex, networked system, haveincreased in number and complexity.

Considering the time constraints, handling changes in a sustainable perspective entailscoping with a dense situation, or rather dealing with the complexity of a collaborative learningprocess that involves all the stakeholders. In the next pages, why and how design should be adiscipline 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 facilitateconnections 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 recalldisciplines by their own nature situated at the edge of different competences domains. Designdiscipline is one them. There is a need for integrating competencies, labelled by Gell-Mann as “acrude 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 fieldsactivating a trans-disciplinary circulation of concepts (Pizzocaro 2000), is made. This meansadopting and developing a new attitude based on a theoretical framework that overlaps systemsscience and complexity theory (Findeli 2001). Designers should use their skills to facilitate theemergence 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 andimprovable (Scagnetti et al. 2007). It has been argued (Friedman 2003; Manzini 2004) thatDesign has gone through multiple phenomenons that have reshaped its meaning and its nature.Designing within Complexity, in fact, involves both substantive and contextual challenges, fromthe increasingly ambiguous boundaries between artefact, structure and process to theincreasingly large-scale social, economic and industrial frames. This could be seen as the needto 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 requiresconsidering the impossibility to reach an exhaustive knowledge of the system in which oneoperates. It could be passed by developing a strategic stance that allows facing the systemchanges and evolution. Designer's key competences: see, show, fore-see (Zurlo 2007) couldbecome 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 informationreferring not solely to the communication of quantitative information but also of intangible valuesand qualitative data.

3. Communication Design and social Complexity

We assume that design interventions could produce changes and transformations both inorganizations that start them and in the complex systems in which they are performed. It ispossible to state that evolution in organizations, here seen as social complex systems, andcomplex systems detract themselves from analytic logic rules and could not be leaded withsimple 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 evenusing unpredictability, dissents and inconsistency. The tasks of all managers are to deal with

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instability, irregularity, difference and disorder. We can suggest that coping with unpredictability isa priority even for Design activities. This new approach leads to start questioning (Kurtz andSnowden 2003) the universality of three basic assumptions that had inspired for long timeorganizational 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 tocountervail them, leading to guess that new tools and modes for managing complexity in humansystems are required. Even though Complexity Sciences provides new paradigm for mathematical and computational system modelling, it could be also seen as a new approach tothe human world. The comprehension of some of complex system structural features (Cilliers1998) 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 agentsconstrained with the environment. Furthermore, one the most important feature is theunpredictability of the system due to its sensitivity to external conditions. Based on theenlightened features a considerable amount of research projects have been carried on mainlyusing 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 limitingcomputational 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 infrastructuresis 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 beidentified by the fragmentation one and is directly linked to the identity issue. Fragmentationrefers to the inhomogeneity (Chapman 2003; Stewart 2001) between social network actors(stakeholders, controllers, influencers, project teams and organizations) involved in systemevolution, making effective communication very difficult. Social complexity requires newprocesses and tools fundamentally attuned to the social and conversational nature of decisionmaking and design work. In this framework a new perspective seems to appear: to enable a moreand more valuable interaction level and dialogue among the actors of a social system. It could beuseful to shape linguistic tools and competences furthering changes rather than predicting andleading them. Focusing this new perspective on that side of Design discipline dealing withlanguages, the Communication Design could face the creation of visual languages affordingrepresentations of Complex systems, easing the spotting of awkward, creating shared visionswithin 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 resourcefulmanner. To act in such kind of domains, increasing the interaction and communication levelbecomes a fundamental action in order to manage and handle changes.

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Diagramming and mapping, typical communication design artefacts, could facilitate to facethe proposed challenge (Abrams and Hall 2006). Diagrams as devices for shared strategies andevaluation of projects impact have an enormous potential to improve decision making processesthanks to their ability to involve all the actors, overcoming the possible hurdles created byspecialized knowledge and languages. This definition of diagram includes all those artefacts

(maps, scenarios, charts, storyboards, etc.) featured by a revealing capacity, a diagrammaticattitude finalized to the act of design (Scagnetti et al. 2007). Diagrams from this viewpoint couldhelp designer to shape clearly complex problems, they are media between what is known about asystem, 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 reflectionsdeveloped 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 nonhomogeneous, 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 willbe represented is made: it is a political stance, intentionally structured and thusarbitrary.

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 performedabout information gathering and transformation. To design diagrams, information and data mustbe collected from different disciplines, with the aim of collecting not only an extensive knowledgeabout 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, theyseem to be comparable in the way they treat information, or, to be more exact, in the way theyallow 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 aparameter to “measure4 complexity”. An interesting way to quantify complexity is the length of amessage to describe a certain feature of a system. It referring to a description could be nothingbut a subjective property. Complexity, however defined, is not entirely an intrinsic property of thedescribed entity; it also depends to some extent on whom or what is doing the description. Theobserver and the system are in a relationship. As a more general definition (Bar-Yam 1997) wecould present that an observer is a social complex system, which through interactions retains a

4 The number of ways of measuring complexity has grown fast. This multiplication of measures has been taken by some to indicateconfusion 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 thisorganizational structure.

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representation of another system (the observed system) within itself (Pizzocaro 2004). Obviouslynecessary condition to adopt this measure is to adopt a language intelligible to the actorsinvolved 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 extensionadopted in describing the system. Furthermore, considering diagrams as picture shapingrepresentation of complex systems, in order to design them it is required to provide conceptualand 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-actorsorganization, involved in handling changes in complex system, as the observer of the samesystem. Obviously, multi-actors organisations are here assumed as social complex system. Thepresented tools, which will be discussed throughout the paper are to be considered as adeepening 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 withcommunicative goals.

4.1. Framing.

The representation of a Complex system presents several difficulties arising from itsstructural features. In order to achieve an interpretative model on how the knowledge aboutsystems could be organized and depicted is appropriate to define a key concept: Complexsystems are usually open and interact with the environment they live in. This concept implies thatit is difficult to clearly define the space where information should be gathered; therefore, it couldbe 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 informationto make the system manageable and describable. It is important to notate it is more helpful to usethe term frame rather than the word boundary . Boundary recalls a piece of land within a fixedlimit, 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 arguedthat (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 couldbe identified on a geographical or territorial base, a more faded term is required: frame could bethis 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.

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A good framing action might be based on the system behaviour perception. In other words itanswers 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 purposeand therefore affected by biases, interests and vision. Cilliers (1998) explains this conceptthrough 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 evolvethrough time, but past events are co-responsible of present behaviour. Ignoring the timedimension could produce inaccurate representations, synchronic snapshot of diachronicprocesses. Such kind of action is a very delicate one. There is a need to communicate and sharehow the framing process has been performed in order to discuss and to create consensus amongall the actors involved in a specific design process. The action of framing ensures the system isdefined in both relevant and manageable way, working on the domain extension field is wanted tobe known.

4.2. Graining

In order to manage the description of the system, what information accuracy will beconsidered, 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 actionconsidering the amount of sensible data much greater than the available, perceptible andintelligible one. Even if we assume the possibility of obtaining all the information about a complexsystem it will be almost impossible to use it, since it creates a situation of information overload 6. Furthermore, analysing a complex system implies the acquisition also of noisy and incompletedata. Their huge amount, its noisiness and incompleteness if associated to a lack of selected andmonitored data, constraints the system describer to a cumbersome filtering and sievingprocedure.

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, creatinggrained observation of the system at a resolution that shows the overall pattern of the system andthe pattern of the elements in it. It is a crucial process for highlighting the regularities immersed inthe observed system7. Adopting graining as conceptual tool, however able to transform the waywe look and act in complex systems, it is possible to set two end points of a continuum where thevarious 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 acoarse 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, afine 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 depicthow it works. In addition, another example could be given (Gell-Mann 1995): envisioning taking awhole picture of a complex system in order to spot on a very small detail, the observer shouldzoom 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 tovarious synonyms and related terms as for example cognitive overload, sensory overload , communication overload, knowledgeoverload, 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 (likea pen). This is enormous (≈ 1022). However, in order to describe the motion of a solid object, we just need 6 degrees of freedom. Wehave then a very much reduced “coarse-grained” description in terms of many fewer variables. So, we need to understand how moreappropriate effective degrees of freedom, such as the translational and rotational ones of the rigid body, emerge and offer a moreappropriate description of the dynamics. Of course, the coarse-grained description is not exact. How the resultant loss in precisionaffects the description depends on what one wants to know about the system.

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and instead of distinguish the desired object, he will only perceive a group of stains. From thisexample 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, andthen by a diagram. This means valuing the complexity of a system based on its description isfunction 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 decidedupon unambiguous and rational choices but rather by the describer. As a general rule commonsense should be used to distinguish between observable and unobservable quantities,manageable and unmanageable. As the coarse graining is subjective, so measurements areinherently subjective operations (Bais and Farmer 2007). Graining helps in addressing thefollowing 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 ComplexityScience uses it to explain some of its operations, in this framework it has to be considered as aneffective 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 thepurpose 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 toacquire, compare, and store information concerning the environment for future use. Furthermorethis 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 successfulrepresentation, and consequently a good visualization. The framing action as well the grainthreshold level should be tuned on the purpose and the questioning wills about the system inwhich intervenes, avoiding senseless and uneconomical processes. For instance to trace aneconomic system is useless to know all about the movements of every penny or Euros even if allthe economic system is a pattern of movements of penny or Euros clusters. The cost to traceevery agents, data, information or relationship is higher than the profit it could generate, the costshould 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 somedifficulties 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.

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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 complexityinvolves 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 anacceptable way to intervene in it – the problem. Since open problems have no stopping ruleending when “good enough” solution is reached (Simon 1996), it is also useful to say that eventhe framing action and the graining process could end only when it is found a good enoughresolution satisfying all the actors involved in the system representation or in the designintervention.

4.4. Scaling

Operative instructions able to visualize phenomena could be mutated from a cartographicapproach. Among the various tools provided by cartographic repertory, scale is a very useful toolin managing also visualization of Complex Systems. It chooses the scene and the viewpoint to bevisualized. The scaling process does not affect the representation of the system, informationgathered will be still available even thou they will not be depicted: like a movie-camera, trough thescale 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 depictinformation. The setting of the scale level consists in an operation that aligns the distance fromthe 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 knowa system, instead it define how a system will be communicated; scale does not require an objectto be know but a several object to be depicted.

Cartographic scale is becoming “visualization” scale (Montello 2001). The concept of scale isoften 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 particularlyinteresting features in order to accomplish a communicative goal (Lam and Quattrochi 1992). It isuseful to remarks that choosing appropriate scale level, again, can only be decided in empiricalway. 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 assynonyms 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 interestexists.

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5. Case Studies

An empirical verification about the use and the application of the proposed tools has beenperformed in a didactic laboratory, the Density Design Lab11. Established in September 2004, thelab 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 theclass. 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 withand to verify the effective complexity. The whole group manage the data collection as well as theproblem setting phase, under the supervision of an external advisor 12. We choose topiccoherently to students interests trying to explore relevant socio-political issues. In the last editionstudents 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 identifysome possible evolutions of the system student coping with, and a communication strategy toactivate the evolution, the whole design experience is reported on the blog13. Even if we try toafford a fully understanding of the system and a relevant data gathering, the laboratory cannotprovide a real decision making process albeit the decision table is simulate and the real actorsoften involved.

5.1. Frame setting discussion

All the six studied system were represented by real data, only the hospital system wasrepresented abstracting it, creating an ideal model. In this case the framing has been set to thephysical bound of the ideal hospital. Framing seems to be reasonably well defined, attuned to thepurpose of the system description, namely to understand the relationship between the hospitalstructure and the patient emotions. In general, framing process has been determined by spatiallimits: national extension for cinematographic, media and infrastructure ones, internationalframing for the fashion system.

Some consideration emerged about not appropriate framing choose: in cinematographicsystems, the frame should be extended not only to the production chain (producers, distributionand directors of film) but considering hidden actors also, like political influence and religiousinterferences. It has to be admitted, the difficulty to grasp such kind of information hindered thepossibility to consider, and then visualize, relevant connections within system. So the framingresulted too tight considering the initial cognitive objective: to discover how the financing processin the system is performed.

Contemporary art system suffered a similar situation: referring the representation only to theItalian territory without considering the international echo connected to their scope, it was almostimpossible 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>

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http://densitydesign.org/

http://densitydesign.org/



The fashion system case introduced time variable into framing process, limiting therepresentation to the last 5 years, which can be consider a relevant period in the fashion systemevolution.

In the infrastructure system the frame seems to be well defined, focusing on the Italiancontroversies which new infrastructures planning and implementation create at local level.Students considered also the correlation between European laws and normative regulating theinfrastructural network development.

Purpose Framing Graining Scale

Italiancinematographicsystem

Are the financings managedor influenced by subjectswhose individual affairs are inconflict with the role that theydress again inside thesystem?

Nationalextension, onlyfocussed onproductionchain

Fine:single director and movie

Not provided

Fashion system Do fashion capitals still makesense? Moreover are therenew actors on theinternational scene?

Worldwide, 5years Coarse but“deformed” Not provided

Contemporary artsystem

Which are the relationsbetween influencers and thevalorisation mechanism?

Nationalextension

Medium Not provided

Hospital system Which is the relationshipbetween the hospitalstructure and the patientemotions

Physical boundof the hospital

Very coarse:groups,hierarchies,protocols of the

structure

Attuned to thecommunicativegoals.

Italian medialandscape

Are users reached only byfew editorial groups? Is thesame content provided indifferent ways giving a wrongidea of pluralism?

Nationalextension

Fine:Editorialproducts

Not provided

Italiantransportationinfrastructuresystem

Which is the dynamic leadingto controversies developingnew infrastructures?

Nationalextension, EUextension for laws andnormative

Medium:Groups andinstitution,impact, % of projectprogress, cost

Some cluster of information werebeen depicted muchin details thanneeded

Tab. 1 Resume of the system representation and visualization purpose and frame, grain settingparameters

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Img. 1. The Italian transportation infrastructure system diagram and some close up

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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 beenapplied detailing all the single film and director. The result is a huge quantity of single data notrelated each other; a coarser graining description of the system, investigating aggregationsinstead of single elements could better give sense to the influences affecting the productionchain.

The approach to graining process has been different: sometimes very coarse (hospitalsystem), sometime fine (contemporary art system). In other cases a middle level has beenchosen: in infrastructure system grain, as in the fashion one, referring only to institutional agentsand aggregate data. It has to be said, in the fashion system, due to unavailability of data thegraining level has been “deformed”. Infrastructure system group sets the grain threshold startingby 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 andcost.

Often the relationship between framing and graining is very close as the case of the hospitalsystem. The need to understand how an hospital works and which is the role of the patient, asstated in the investigation hypothesis, a very coarse level of grain has been required:representation concerned only the dynamics between different hierarchies and protocols of thestructure. A finer graining level would have compromised the disclosure of the purpose, tounderstand the general mechanism of the hospital, and to trace every single individual agentswould have masked the overall dynamic of the system.

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Img. 2. The hospital system diagram and some close up

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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 muchdetails, 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 thediagram 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 thestructure 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, somecluster 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. Tosum up: the tools requires those who have to cope with complex issues to understand what is thepurpose of system representation as well to stimulate a shared vision of it even through the useof framing, graining and scaling processes.

The framework proposed has been refined trough 4 years of didactic activities, leading tosome limits, both logistic and related to the availability of only secondary resources. Thereby inthe case studies, the use of time as a framing parameter has been affected by the lack of a realdecision- making table and it has not been properly explored.

Overall, the experiments enlightened the effectiveness of the proposed tools, providing thestudents whit clear reference to approach complex systems. The processes proposed, negotiatedwith the teaching body and the experts, and emphasized the need of a recursive definition inorder to share it. It has to be admitted that in some case the expected data availability affectedtoo 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 nonacademic contexts14.

Some difficulties have to be noticed in the communication of the parameters setting toexternal actors to whom visualization have been presented, but in general term the diagramseffectiveness as facilitation tool has been well valued. Furthermore, it could be useful to designproper system to label visualization, developing new kind of legend. Information about how theframing, graining and scaling process have been performed, should be taken into account in thisnew kind of notation, in order to provide a clear explanation to all those who have to work withdiagrams 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 WorldDesign Capital 2008. Further detail are available here: <http://www.torinoworlddesigncapital.it/portale/en/content_2.php?sezioneID=288&ID=437&categoriaID=382>

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Documents

02b Dossier Appendix Handling Changes Through Diagrams