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Visualization Types Codex

By Peter Stoyko
Complex systems are difficult to understand without the
aid of visuals. There are too many moving parts to mentally
keep track of. The parts interact in too many ways. The whole
system is cognitively overwhelming insofar as it cannot be
absorbed in one go without the aid of an external reference.
That is partly due to humans' inability to juggle more than
a few complicated ideas in working memory at one time.
Thus, visuals are a simplifying and organizing device that
complements the way human naturally think if they are
designed well. This poster is an early glimpse of a larger
project (called SystemViz) that explores what it means to
design such visuals well.

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Visualization Types Codex

  1. 1. D E S I G N + V I S U A L T H I N K I N G V . 0 . 5 - B B Y P E T E R S T O Y K O THE CHALLENGE Complex systems are difficult to understand without the aid of visuals. There are too many moving parts to mentally keep track of. The parts interact in too many ways. The whole system is cognitively overwhelming insofar as it cannot be absorbed in one go without the aid of an external reference. That is partly due to humans' inability to juggle more than a few complicated ideas in working memory at one time. Thus, visuals are a simplifying and organizing device that complements the way human naturally think if they are designed well. This poster is an early glimpse of a larger project (called SystemViz) that explores what it means to design such visuals well. TAKING STOCK OF VISUAL METHODS. The first challenge is that there are many ways to display systems visually. Diagram formats and notations have proliferated. Some correspond to particular disciplines or tasks. Each has innumerable minor variations. It is worth taking stock of these "visual vocabularies" because the choice of visualization method skews the way systems are understood. Different methods emphasize different things and removes certain details from the picture: all are, by definition, a form of reductionism; all contain implicit assumptions about what a system is and how it behaves. For example, one method may depict systems as stocks and flows, another may depict them as logical sequences; another as causes, effects, and two-way dynamics; another as signals and boundaries. These differences depend on the underlying theory in use, but also the unthinking tendency to adopt a visualization method out of convenience or habit. The result is a paradox: without visuals to help model systems, understanding is limited; visual conventions frame the way systems are understood, which can undermine understanding. Thus, the first task of this project is to provide an inventory of the various visualization methods by grouping them according to their main points of differentiation. This is a first approximation. The aim is to solicit feedback about this way of organizing visuals and determining if there are major errors of omission. The aim is also to have a discussion of the biases and blind spots of the respective methods. IDENTIFYING MISSING CONCEPTS. There are many systems concepts that are applicable across practical and academic disciplines. The overall literature is wide and deep. Some concepts are wide recognized; others less so, partly because of a lack of trans-disciplinary engagement. That presents an opportunity for visuals to act as an interdisciplinary lingua franca. That also raises some important questions: What systems concepts are not easily depicted using conventional methods of visualization? Identifying these concepts is the second aim of the project. The hope is to start a conversation about visualization methods that might fill these glaring omissions. EXPLORING VISUALIZATION CHALLENGES. Creating an inventory is an opportunity to reflect on recurring problems and trade- offs. That is the third task of the project. The goal is to provoke a discussion about ways of overcoming these difficulties. A few lessons from the discipline of information design provide partial guidance. The ultimate goal is to turn these stock-taking exercises and "guide posts" and turn them into a design and teaching tool (a "codex") in an appealing and accessible form. This post is an early step in that direction. Inspiration is drawn from David Garcia's Manual of Architectural Possibilities series of road- map-like foldable posters. Interactive, screen-based versions may also emerge. If the project yields some interesting techniques, the goal is to make those openly available to members of the larger community interested in systems thinking. Peter Stoyko is an interdisciplinary social science and information designer at Elanica, a management consultancy that specializes in service design and governance. Feel free to contact him at peter.stoyko@elanica.com or visit the project page at systemviz.elanica.com. ? NO-NAME CONNECTIONS Unspecified links between items make relations and dynamics ambig­uous, often suggesting analytical evasion. Link labels, badges, symbolic ends, or encodings (e.g. color coding) indicate nature of link. // FIX // VISUALIZATIONHURDLES VISUALIZATIONTYPES SPAGHETTI TANGLE Unmanageable links between objects makes it difficult to distinguish relationships. Prioritize and differentiate lines. Use layering techniques. Add visual affordances to guide the eye. // PARTIAL FIX // STATE EXPLOSION Unmanageable numbers of diagram nodes, especially for number of potential states in Petri nets. Increase level of abstraction at the cost of precision. Use different levels of analysis for crucial details. // TRADE-OFF // EVERYTHING CONNECTED The temptation to connect everything to everything else because, at some level, a relation can be imagined. Rank and differentiate relationships according to well articulated analytical priorities. // FIX // FALSE EQUIVALENCE Failure to sufficiently differentiate linkages creates mistaken impression of equal importance. Differentiate lines in ways that convey magnitude and qualitative differences. Add text labels and numerical weights. // FIX // NOTATION OVERLOAD Number of symbols and distinctions exceeds viewer's ability to differen- tiate and juggle in working memory. Reduce number of encodings, especially for minor distinctions. Do not rely on legends. // PARTIAL FIX // PERCEPTUAL SIMILARITY Basic shapes used in diagram are not sufficiently differentiated so that important distinctions are overlooked. Use shapes (and other encodings, such as color and text style) with higher levels of contrast. // FIX // ETHNOCENTRIC SYMBOLISM Symbolic visual objects (such as icons) carry cultural meanings that are not universally understood. Research cultural background of symbols. Use symbols recognizable across cultures. // PARTIAL FIX // SUBJECT MISMATCH Diagram method is poor fit to the nature of the subject matter because of mismatched theory of use. Use more suitable method. Abandon highly standardized notation for more bespoke graphics. // FIX // NEGLECTEDCONCEPTS? A C E E L J J Z A M C 4 5 6 7 M 4 5 6 Perforated Collection Tube Fresh Water Reverse Osmosis Membrane Pressure Vessel Concentrate Fresh Water Feed Water Fresh Water LINKS BETWEEN OBJECTS SHOWING CAUSAL DIRECTION, MOVEMENT, OR SEQUENCE FLOW TRANSITIONPETRI NETS AND OTHER MATHEMATICAL GRAPHIC NOTATIONS SHOW SYSTEM PHASES WITH PRECISION LOOPSTOCKS, FLOWS, AND SYSTEM DYNAMICS ARE MAPPED AS LOOPS SITUATESYSTEM DIAGRAMS ARE LAYERED OVER MAPS OF PHYSICAL SPACE AND OTHER DIAGRAMS ARRANGENODES AND LINKS ARE ARRANGED AND CATEGORIZED WITH VARIOUS SPATIAL ARRANGEMENTS EXPLAINILLUSTRATED DIAGRAMS SHOWS HOW A SYSTEM WORKS BY MIMICKING REAL-WORLD APPEARANCE Geothermal Heat Magma Condenser Steam Hot Air & Water Vapor Waste Water Groundwater Replenishment Top-up Injection Well Production Well Impermeable Rock Cooling Water Impermeable Rock Conductive RockConductive Rock Groundwater Infiltration High Lands Water Run-off Warmed Water Cooling Water Power Transmission Power Generation Power Transmission Rain Water Coastal Winds Pump Turbine Generator Water Treatment Cooling Tower Households Transformer Condensate Heated Aquifer LIKENVISUAL ANALOGIES COMPARE SYSTEMS TO OTHER SYSTEMS THROUGH BLENDING EXPOSEPART AND WHOLE RELATIONSHIPS OF SYSTEM ARE SHOWN REALISTICALLY THROUGH CUT-AWAY AND EXPLODED VIEWS YES NO NO Motion detected Animal? Human? Guard? Isolate Individual Remove Individual Escort to Office Send to Office On Duty? Machine? Beacon? Alone?Record Number Valid? Danger? Isolate Machine Escort to Lab Guard Check Continue monitoring YES NO NO NO NO YES YES YES YES NO NO YES NO YES YES Report Incident Input Reason Sound alarm Remove Machine G E N E R I C N O T A T I O N PROCESS DECISION DELAY PROCESS FLOW TERMINAL DATA PROCESS GROUP DISPLAY MANUAL INPUT TRANSFER MANUAL LOOP LOOP LIMIT CONDITION ORGANIZATION PREPARATION STORED DATA DOCUMENT PARALLEL MODE SUB-PROCESS CONNECT SORT MERGE COMMENT AND Text CHECK COLLATE TO PAGE OR JUMPREFERNCE Intelligence Gathering Product Specifications Prototype Refine User Testing Tester Screening Test-site Preparation Outreach Implement Participant Recruitment Data Requirements Field Research Findings Reviewed Advisory Review Study Prepared Finalization Client Needs Assessment Client Feedback Stakeholder Mapping Product Launch Participatory Research R1 Integrative Learning B1 Product Development R2 Knowledge Mobilization R3 Iteration R1b Iteration R2b Testing R3c Tweak R2c ( Arita, 49 ) ( Ito, 21 ) ( Nishi, 31 ) ( Fukuyama, 42 ) ( Takeuchi, 38 ) ( Enomoto, 26 ) ( Sakoda, 55 ) Request End Submission Process Flag Expedited Submission References Checked Record Ready Request Routed Request Filed Record Reviewed Add More References Process ( Matsuki, 22 ) CAUSAL LINK POSITIVE EFFECT DYNAMIC LINK NEGATIVE EFFECT LOOP LABEL BOUNDARY DELAYED EFFECT FLOW OUTFLOW BIFLOW A2 BALANCED LOOP (OR )B REINFORCING LOOP (OR )R FLOW RATE OR OR G E N E R I C N O T A T I O N STATE STATUS OF SYSTEM ITEM PSEUDO STATE EXOGENOUS STATE SEE SCHOLARPEDIA ARTICLE INSERT TRANSITION CHANGE TO NEW STATE SUBSYSTEM MULTIPLE PARTS TO STATE OR TRANSITION DELAY IN NUMBER OF TIME UNITS TIME STAMP START OF MOVE IN TIME UNITS TOKENS OBJECT MOVING THROUGH SYSTEM TOKEN LABEL DATA SEPARATED BY COMMA @+3 3 G E N E R I C N O T A T I O N M U LT I P L E L A Y E R S L A Y E R E D L E V E L S O F A N A LY S I S E X P L O D E D C U T A W A Y THE FOLLOWING ARE SOME EXAMPLES OF SYSTEM CONCEPTS THAT ARE BEING COLLECTED AS PART OF THE PROJECT TO SEE IF EXISTING VISUALIZATION METHODS CAN ADEQUATE- LY REPRESENT THEM. CURRENTLY, THE DATABASE HAS APPROXIMATELY A HUNDRED ITEMS GATHERED FROM ACROSS NATURAL AND SOCIAL SCIENTIFIC DISCIPLINES. ATTRACTOR An element that draws others towards it or distorts its trajectory through an attractive force. REPELLER An element that pushes others away or distorts its trajectory through repelling force. SIDE EFFECTS Externalities or unanticipated consequences caused by a force or dynamic between two objects. DISTAL DRIVER A background cause observ­ able at a high level of analysis ("bigger picture"); a diffuse factor acting on more obvious factors in a causal chain. KLUDGE A make-shift work-around to cope with an immediate problem, adding variation (often complexity) to system; source of "jagaad" innovation. ENABLER A factor that gives another factor a boost, either as a necessary ingredient or as a contributing one. PROXIMATE DRIVER A variable that directly causes another variable to change; that is, an immediate cause. FRICTION A factor that impedes another factor directly to blunt, delay, or skew. An obstacle that prevents a variable from running its course by affecting other variables in a causal chain PROTECTOR A blocker that preserves the state of a variable from some or all outside influences Boundaries Signals CONTAINER A boundary that groups items discretely by separating them from others SEPARATOR A boundary that separates or differentiates two groups or areas SEMI-PERMEABLE A boundary that blocks certain factors but not others depending on their qualities BOTTLENECK A boundary that limits the throughput of forces through an area or process DIVERSITY BETWEEN The variation between different categories of object DIVERSITY WITHIN The amount and quality of variation found within a single category of object Factor that has to be present for one thing to cause another to change, perhaps part of the environment PERSPECTIVE How the system changes depending on the vantage point or qualities of the viewer. SENSING Parts of the system that receive signals from the external environment or elsewhere in the system. INPUT/OUTPUT Parts of the system that take in or expel factors from the outside. COMPATIBILITIES Aspects of a system that are able to interact functionally or to mutual benefit because of compatible design features PARASITE An outside agent that derives benefit from an host or system while imposing costs Relations DomainsForces PROCESSCONCEPT DATABASE Sort Store Store Form Status No MergeNew? B A A X B Sort Start Sort Pump X Archive Activity Match Report Inspect Soya G HJ L K AM N F Water Land Market Soil Sun C G1 C2 P2 P1 C3 G2J1 K1 2 J2 P A B M2

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  • jjxdev90

    Jul. 20, 2018
  • DiarmaidUpton

    Jun. 10, 2020

By Peter Stoyko Complex systems are difficult to understand without the aid of visuals. There are too many moving parts to mentally keep track of. The parts interact in too many ways. The whole system is cognitively overwhelming insofar as it cannot be absorbed in one go without the aid of an external reference. That is partly due to humans' inability to juggle more than a few complicated ideas in working memory at one time. Thus, visuals are a simplifying and organizing device that complements the way human naturally think if they are designed well. This poster is an early glimpse of a larger project (called SystemViz) that explores what it means to design such visuals well.

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