Affinity Diagramming

or the KJ method

Affinity diagramming is a conceptual organizational exercise that can have numerous benefits for problem solving in team environments. Ideas are not only identified by a group, but then explicitly categorized and grouped. Enumerating instances and aspects of cultural phenomena—and categorically naming them—identifies trends and highlights differences. A phenomenon, whether it is a behavior or a problem or both, is best understood when the interlocking parts of the system can be made explicit.

History and Theory

Affinity diagramming was developed by Jiro Kawakita over the course of fifteen years while he was conducting ethnographic research in the Himalayas. Its popularity in Japanese management culture spread primarily through its introduction at the Free Campus University, at which Kawakita was a professor (Scupin 233-234). The KJ Method is the application of affinity diagramming, or the formalization of verbal/written procedure. Kawakita’s proposition suggests a connection between unstructured observations and scientific hypothesis testing or experimental design, which heretofore was arcane and non-specific (10).


“An affinity is built from the bottom up by first grouping similar observations, labeling them, then building larger groups out of these small groups” (Beyer 30).  Team members—ideally a group of several—will follow three steps to create the affinity, and additional step of analysis or reflection. Scupin describes the steps as label making, label grouping, chart making, and analysis (235). The following descriptions for each step are an amalgam of the KJ Method as described by Hoerl & Snee, Scupin, Kawakita himself, as well as experienced by a tutorial given by Professor Kristian Kloeckl at Northeastern University in October of 2016.

I. Label Making

Assemble a group of several participants. Hand out pieces of paper, big enough to write a sentence or phrase on, to each participant. Post-It® notes work as well. Clear a board or wall or a table to act as a canvas. Label the center of the canvas with the problem/phenomena concisely. Allow each participant to brainstorm ideas, concepts, objects, actors, interactions, behaviors, emotions, or related phenomena associated with the target problem/phenomena. As a participant thinks of an idea, they write it on an individual piece of paper, verbalize it to the group, and adhere it to the canvas in no specific place. Do such until the enumeration begins to slow down.

II. Label Grouping

Then, the team begins to group the ideas on the canvas by whichever criteria seems rational. The team does this simultaneously and silently. Participants are encouraged to group, regroup, split and combine papers on the canvas despite another participants opposing groupings. Once a distinct amount of groups emerges—or participant consensus or attention fatigue sets in—the grouping phase is over.

III. Chart Making

Once the groups of paper have been established, participants begin to devise titles or categorical names for the groups of labels. In discussion of titles, individuals can propose titles that restructure, or oppose the groups of labels made in the previous step. If any phrase or concept is perceived as an outlier, it is helpful to have the author explain the experience that led them to include this. Often these clarifications lead to the outlier being fed into an existing group, or expanding another grouping’s title. Once every grouping of concepts has a title, larger structural questions should be asked: do certain groupings fall completely within others? and do certain groupings share common traits with other label groups? Arrange the chart utilizing structural visual metaphors, such as inclusion/subset, opposition, or union.

IV. Analysis

No affinity diagram is complete without analysis. Kawakita recommends an analysis that is both concise and smooth (12).  A verbal and or written explanation guides the team in distinguishing the interpretations from the descriptions. It reduces the complexity of the enumerated labels into a form that is manageable and consumable by parallel participants, or amateurs, or clients (Scupin 236). The analysis can begin to explore what labels are causes and which labels are effects. Additionally, the analysis can provide guiding structural vocabulary for a team enacting a solution appropriate for a context laid out in the affinity diagram.



I. Label Making


Participant members Irene De La Torre, Jessie Richards, and Andrew Tang produced this affinity map under the facilitation of Patrick J. O’Donnel. The behavior explored was the “Pedestrians Crossing the Street,” ultimately fulfilling a larger study of waiting in urban contexts. Enumeration of actors, technologies, places, concepts, behaviors, interactions, emotions, and rationales plotted the range of data that comprises a pedestrian waiting and crossing the street. Post-it notes were given to each participant. As each concept was written down it was announced to the room, without concern of redundancy or judgment. The canvas filled up, and the generation of concepts slowed, after about seven minutes.

II. Label Grouping


During the silent phase, labels were moved frantically about. The most intriguing behavior was the use of space outside of the canvas for organization—like the wall the white board was attached to, and a nearby table top. Our canvas was full at the end of the label making, but white space between semi-grouped concepts seemed promote the cognitive function of organization while not overwhelming the visual search. A few participants found themselves picking up a label, trying to make it fit in, only to hand it off to another participant, in hopes they had a connection that sparked upon it being received. The result was nine groupings of concepts.

III. Chart Making


After reaching wa—a Japanese word for the harmony that arises from group consensus (Scupin 234)—the facilitator broke the silence with talks of categorization of the most obvious groupings first. To make titles for these groupings, the participants discussed each group individually. A natural reaction to a conceptually sound grouping was the instantaneous offer to suggest a title. If several iterations of a title could be suggested, more often the title was selected from them.

If the brainstorming of titles did not immediately yield results, the facilitator asked if there was an outlier in the group that is holding back a near-inclusive title. At this point, the creator of the outlier label gave a brief explanation as to why they included it initially. Usually this type of clarification guided the group to move the label to another grouping, or brainstorm an inclusive title. Once grouping titles were agreed upon, the post-it notes were circled by dry erase marker, to signal its completeness. The results for the pedestrian crossing diagram was category titles such as “actors in compromising safety,” “timing,” and “crosswalk awareness.”

IV. Analysis

The context charted by the affinity diagram shows a concern with human-recognized objects (actors and technology), actor concern for safety, and acts of crosswalk system awareness. Though the time spent waiting at a crosswalk is relatively low compared to the totality of an average pedestrian journey, a consciousness of system temporality was apparent. The participants also grouped system signals and distracting stimuli in a group called “crosswalk awareness” that suggests distraction and information-retention exist on a spectrum, and vary in attention from person to person or trip to trip. The amount of stimulation at a crosswalk can actively compete with each other. Additionally, many artifact and architectural labels were grouped, suggesting that actors are aware of the regularity/design of crosswalk intersections.

Pedestrians crossing the street is a context more nuanced than just an exchange between pedestrians and traffic that results in waiting. The improvisational behaviors of pedestrians making judgments about how to opportunistically jaywalk is a complex algorithm that is shaped by the “cognitive mind extension” described by Clark and Chalmers. The systems of trains, automobiles, cyclists and pedestrians all emit visual and sonic stimuli that, when subconsciously processed, is helpful—and life-saving—but, when attended to, is stress-inducing. Some might say these stimuli are even a symbolic epitome of hurriedness in urban life. The affinity diagramming brought about the considerations that constitute a context in which potential interventions and solutions can be embedded.


Beyer, Hugh. “User-centered agile methods.” Synthesis lectures on human-centered informatics 3.1 (2010): 1-71. Morgan & Claypool Publishers. Web. 17 Oct. 2016.

Clark, A. and Chalmers, D. “The extended mind.” Analysis 58, 1 (1998), 7–19.

Hoerl, Roger, and Ron D. Snee. Statistical thinking: improving business performance. Vol. 48. John Wiley & Sons, 2012. ProQuest. Web. 14 Oct. 2016.

Kawakita, Jiro. “The original KJ method.” Tokyo: Kawakita Research Institute (1991). Web. 17 Oct. 2016.

Scupin, Raymond. “The KJ Method: A Technique for Analyzing Data Derived from Japanese Ethnology.” Human organization 56.2 (1997): 233-7. ProQuest. Web. 14 Oct. 2016.




Readings Beh/Exp W6

Readings Week 6
Design for Behavior & Experience
Patrick J. O’Donnel

Verbeek, Peter-Paul. “COVER STORY Beyond interaction: a short introduction to mediation theory.” interactions 22.3 (2015): 26-31.


    1. There are three approaches (or philosophies) to considering the human-technology duality: technology as extension, technology as dialectic, technology as hybridization.
    2. Don Ihde categorizes human-technology relationships as embodiment, hermeneutic, alterity, and background relations;  Verbeek proposes the existence of a three additional categories for relationship: cyborg and (embedded) interaction context and augmentation.
    3. If designing technologies is designing the mediation of the human-technology-world triad, then designing must be understood through an ethical lens. Verbeek recommends that designers should anticipate mediations and adopt libertarian paternalism philosophies while creating. Shying away from mediations won’t benefit society; literacy and responsibility of mediations is the only path forward.


    • “Still, interaction might not always be the most helpful concept for understanding the relations between humans and products, or for understanding technological artifacts in general. Recent insights from the philosophy of technology, specifically from the approach of ‘technological mediation,’ lead us to rethink the relations between humans and things, shedding new light on the field of interaction design.”
    • “[H]umans and technologies should not be seen as two ‘poles’ between which there is an interaction; rather, they are the result of this interaction.”
    • “Designing technology is designing human beings: robots, vacuum cleaners, smart watches—any technology creates specific relations between its users and their world, resulting in specific experiences and practices.”
    • “(Some) technologies do much more than merely function—they help to shape human existence.”
    • “Seeing technologies as more than neutral opens the door to arguments like “the machine made me do it” (Joe Pitt).
    • “Cognition, they claim, cannot be limited to the human mind, but rather is extended to the material artifacts people use, such as agendas, computers, and even brain implants: They help us to think, remember, and have experiences” (Andy Clark & David Chalmers).
    • “In Ernst Kapp’s philosophical-anthropological approach to technology, for instance, technologies are seen as projections of human organs. A hammer is a projection of the fist, a saw of teeth, and the telegraph network—the high-tech of his day—of the human nervous system.”
    • “Technologies and human beings help to shape each other. Technologies are an element of human nature: They are part of us.”
    • “(Adoption of the hybridization philosophy of human and technology relations) implies that designers, in fact, do not merely design products, but human practices and experiences as well. Products do not only have functional, interactive, and aesthetic qualities, but are in fact also mediators in the lives of human beings. Designing things is designing human existence.”
    • “In embodiment relations, technologies form a unity with a human being, and this unity is directed at the world: We speak with other people through the phone, rather than speaking to the phone itself, and we look through a microscope rather than at it. […] (human – technology) —> world.”
    • Hermeneutic relations, as Ihde calls them, are relations in which human beings read how technologies represent the world, such as an MRI scan that represents brain activity or the beeping of a metal detector that represents the presence of metal. Here, technologies form a unity with the world, rather than with the human being using them. […] human —> (technology-world).”
    • “In a third type of human-technology-world relations, which Ihde calls the alterity relation, human beings interact with technologies with the world in the background of this interaction. […] human —> technology (world).”
    • “Ihde distinguishes the background relation, in which technologies are the context for human experiences and actions. The sounds of air conditioners and fridges, the warm air from heating installations, the notification sounds from cellphones during a conversation—in all of these examples, technologies are a context for human existence, rather than being experienced themselves. […] human (technology/world).”
    • “A brain implant, for instance, that is used for deep brain stimulation to treat Parkinson’s disease or psychiatric disorders, is not merely embodied; rather, it merges with the human body into a new, hybrid being. I have proposed to call this a cyborg relation: human/technology —> world.”
    • “Other technologies merge with our environment, into ‘smart environments’ with ‘ambient intelligence’ and sometimes even ‘persuasive technologies’. Here, technologies are not just a background for our existence, but rather an interactive context: They detect if people are present or not, recognize faces, give feedback on behavior. […] human <—> technology/world.”
    • “Wearable technologies such as Google Glass give yet another human technology configuration. They result in a bifurcation of the human-world relation: On the one hand, smart glasses can be embodied to give an experience of the world, while, on the other hand, they give a representation of the world in a parallel screen. This relation could be called augmentation, combining an embodiment relation and a hermeneutic relation: (human – technology) —> world + human —> (technology – world).”
    • “Steven Dorrestijn has developed a framework to categorize these contact points, using the human body as a reference [13]. He distinguishes four types of contact, corresponding to four zones around the human body: ‘to the hand,’ ‘before the eye,’ ‘behind the back,’ and ‘above the head.’”
    • “Nynke Tromp et al. have distinguished two dimensions in the influence of technologies on human beings: its visibility and its force. The impact of technologies can be located somewhere on the continuum between ‘hidden’ and ‘apparent,’ on the one hand, and between ‘weak’ and ‘strong,’ on the other [14].”
    • “Strong, apparent influences can be called coercive: turnstiles that force you to buy a ticket before entering the subway, or cars that won’t start when you don’t wear a safety belt. Weak, apparent influences are persuasive. Technologies show their influence, without being overpowering: smart energy meters that give feedback on your energy consumption or e-coaching apps that help you lose weight.
      “The hidden types of influence are often seen as a little more creepy, but in fact they are very common. Hidden, weak influences can be called seductive. Their impact is non-cognitive and mild: placing a coffee machine in the hall of a company to stimulate social interaction, using material that ages beautifully to prevent people from discarding a product prematurely [10,15]. The final type of influence is both strong and hidden; it can be called decisive or implicative because it exerts influence without this influence being noticed. An example is an apartment building without an elevator, implicitly forcing people to use the stairs.”
    • “Technological mediation is part of the human condition—we cannot be human without technologies. This makes the design of technologies a highly responsible activity. Designing technology is designing humanity, in a sense.”
    • “Therefore, along with functionality, interaction, and aesthetics, mediation deserves a central place in the conceptual framework that implicitly and explicitly guides design activities.”
    • “Explicitly influencing people via design is a contested thing to do, though. It puts something at stake that has become one of the most sacred things in contemporary Western culture: human autonomy. For that reason, for instance, Thaler and Sunstein explicitly call their approach a form of ‘libertarian paternalism.’ It is inevitably paternalistic, in the sense that it exerts influence on human beings, but at the same time it explicitly aims to be libertarian, in the sense that it always gives people the possibility to opt out. Nudges should never be given invisibly or without the possibility of avoiding them.”
    • “Human freedom cannot be saved by shying away from technological mediations, but only by developing free relations to them, dealing in a responsible way with the inevitable mediating roles of technologies in our lives.”


Dourish, Paul. “Seeking a foundation for context-aware computing.” Human–Computer Interaction 16.2-4 (2001): 229-241.


    1. Wiesel proposed a vision of ubiquitous computing, where embedded processors are cheap enough to manufacture for specific contexts; Ishii & Ullmer suggested a program of Tangible Bits, that connects the materiality of the physical world (atoms) to the materiality digital world (“bits”) by utilizing physical controls of digital information. Both configurations attempt to tie the physical world to the digital world, as well as reduce the barrier between interface and action. Schuman’s “situated action perspective” suggests that humans, as improvisational actors, determine meaning from interaction based on context—cultural, organizational, physical, and temporal.
    2. Phenomenology, the study of phenomena, equates to the study of embodiment. Husserl sought to reconnect science to the real world by explicating a ‘natural attitude’ that makes sense of contexts with meaning. His student, Heidegger, furthered the radical idea that the world was filled with meaning inherently, and as explorers, our actions reveal the meanings already in place. Another student, Schutz, connected phenomenology to intersubjectivity with a common life-world, inside of which, two subjects gain access to a background that permits actions understood as rational.
    3. Embodiment of interactions places interactions inside of meaning; Meaning comes from actions and interactions, and therefore can only be suggested and not directly designed.


      • Why has context-aware technology developed? “ One spur to the emergence of context-aware computing has been the novel technical opportunities afforded by falling costs, sizes, and power requirements for a range of computational devices and associated advances in sensor technology, which jointly allow us to develop new forms of embedded interaction, augmenting physical environments with computation that can be responsive to the needs and activities of the people that occupy them. A second is the recognition of the mutual influence of the physical environment and the human activities that unfold within it, so that aspects of the setting can be used both to disambiguate and to provide specialized computational support for likely action. A third is an increasing understanding on the part of system developers that human activities, including those that we conduct with and through computation, are enmeshed in a variety of practices and relations that make them meaningful by setting a context within which they can be understood and evaluated. A fourth is the influence of design that draws attention to the symbolic as well as the instrumental use of technologies and the roles that each conception of technology need to play in their design and deployment.”
      • “ the idea of computation embedded into the everyday environment opened up the possibility of computer technology receding into the environment and became useful to us (the population) in completely new ways.”
      • “ Ishii and Ullmer observed that we operate in two different worlds— the world of computation (‘bits’) and the world of physical reality (‘atoms’). However, although the world of physical reality is one with which we are deeply and intimately familiar and one in which we are, as organisms, evolved to operate, most interactive systems make very little use of these natural skills and abilities in supporting interaction.”
      • Tangible Bits and UbiComp are similar in a few ways. “First, they both attempt to exploit our natural familiarity with the everyday environment and our highly developed spatial and physical skills to specialize and control how computation can be used in concert with naturalistic activities. Second, they both use spatial and temporal configurations of elements and activities in the real world to disambiguate actions and so make computational responses a better fit for the actions in which users are engaged. Third, they both look for opportunities to tie computational and physical activities together in such a way that the computer ‘withdraws’ into the activity, so that users engage directly with the tasks at hand and the distinction between ‘interface’ and ‘action’ is reduced.”
      • “ Critically, this means that, for ethnomethodology, social conduct is an improvised affair, carried on in real-time in the course of everyday activity. Social conduct is orderly not because it is governed by some overarching theoretical construction but because people make it orderly. Ethnomethodologists argue that people find, within the conduct of everyday affairs, the resources by which those affairs can be found to be meaningful and rational; so in turn, they recommend that the investigation of social order should not take the form of a search for theoretical principles, but rather should involve the careful examination of specific instances of organized action so as to be able to uncover the means by which people produced  the rationality that they exhibit.”
      • “This perspective, in which the sequential organization of conduct arises in response to the immediate circumstances in which it arises, Suchman termed the situated action  perspective, and it stands in contrast to the traditional planning model in which the sequential organization of action is predetermined by an algorithmic exploration of the ‘search space’ of goals and actions. Suchman did not reject the notion of ‘plans’; instead, she observed that plans, as prespecified formulations of future action, are merely one of a number of possible resources that people draw upon in answering the question, ‘what do I do next?’”
      • “ Context— the organizational and cultural context as much as the physical context— plays a critical role in shaping action, and also in providing people with the means to interpret and understand action. Similarly, because the meaning of action is interactionally determined, temporal context is also involved, as actions and utterances gain their meaning and intelligibility from the way in which they figure as part of a larger pattern of activity.”
      • “ Beyond this, we also need to take account of social, cultural, organizational, and interactional context, which are equally telling for the ways in which action will emerge.”
      • “[…] By embodiment I mean a presence and participation in the world, real-time and real-space, here and now. Embodiment denotes a participative status, the presence and occurrence of a phenomenon in the world.”
      • “[P]henomenology, which, loosely, is the philosophy of the phenomena of experience.”
      • Edmund Husserl, the earliest writer on phenomenology, sought to “reconnect science with the real world, and the means by which this was to be done was to develop the philosophy of human experience on a rigorous scientific footing. This philosophy of the phenomena of experience was phenomenology. Phenomenology set out to explore how people experience the world— how we progress from sense-impressions of the world to understandings and meanings. Fundamentally, it put primary emphasis on the everyday experience of people living and acting in the world, and the ‘natural attitude’ toward the world that lets them easily and unnoticeably make sense of their experience.”
      • “Heidegger rejected this idea. He argued that rather than assigning meaning to the world as we perceive it, we act in a world that is already filled with meaning. The world has meaning in how it is physically organized in relation to our physical abilities and in how it reflects a history of social practice. For Heidegger, the primary question is not ‘How do we assign meaning to our perceptions of the world?’ but rather, ‘How does the meaning of the world reveal itself to us through our actions within it?’”
      • “ [M]eaning, for us (humans), arises from the ways in which we engage with and act within the world. I believe that this is of central importance in trying to understand the notion of embodied interaction that lies at the heart of the two aspects of context-based computation discussed earlier and elsewhere in this issue.”
      • Alfred Schutz “proposed an approach to intersubjectivity rooted in our common experience of the world and on the way in which we can interpret and understand the actions and motivations of others by appeal to the assumption of a shared life-world (or lebenswelt) that, first, grounds our common experience and, second, gives me the necessary background to understand your actions as being rational.”
      • “ The design concern is not simply what kinds of physical skills, say, we might be able to capitalize upon in a tangible interface, or what sorts of contextual factors we can detect and encode into a UbiComp model. Instead, we need to be able to consider how those skills or factors contribute to the meaningfulness of actions.”
      • “Most important, the designer does not have absolute control, only influence. In turn, this suggests that if the meaning of the use of the technology is, first, in flux and, second, something that is worked out again and again in each setting, then the technology needs to be able to support this sort of repurposing, and needs to be able to support the communication of meaning through it, within a community of practice.”

Data Stories: Data Sculpture

Data Stores Podcast: Episode 17

Data Sculpture

State of the Art: Part 1

State of the Art: Prior Works Research
Part 1

Thesis key words: Physical data visualization, data installation, data materiality, participatory data visualization

(1) Glue Society – “BT – Longterm Investor”

A series of (TV/digital media) spots using light sculpture to present estimates of investment data.

BT Financial ‘Superannuation’ from The Glue Society on Vimeo.

Materiality: Light

Architecture: digital, sloping, flat

Interaction: None, but animated

Pros: Metaphor equating light with idea and positivity and the future intact; narration clear; mood and graphics align with intended audience

Cons: Numbers not present until the end & their scale is small; light field is essentially flat, no conceivable reason for sloping plane; low resolution data

(2) Bryan Ku – “MB15 Minos”

An interactive installation for Moving Brands that visualized staff members as codified three-dimension, brightly patterned geometric solids based on office location, department, and other facts about the employees.

Materiality: none, digital

Architecture: Operating podium, projection

Interaction: Leap System, hand movements as a signal

Pros: Design of application provided approachability to party-goers; codified system of making able to be discovered (some hints found on side of operating podium); metaphors for socialization strong; integrated live stream of party goers tweets and instagrams

Cons: Lacks materiality; spatial presence brought about by utility; installation competes with experience of party

(3) Bryan Ku – “WIM•BLE•DON”

Flipbook data visualization that operates with a pair of users alternating page turns for the final game of a Wimbledon championship match.

Materiality: Paper, bound book

Architecture: none, mostly flat

Interaction: user-operated, chronological animation

Pros: metaphor in interaction between opponents; sleek visual design; excellent source of storytelling; user-operated creates controlled experience

Cons: unsure how unguided operation would begin; lack of relationship to body or space; experience heightened greatly by video track; assumes knowledge of rules of tennis to communicate story

(4) Doug McCune – “San Francisco Housing Prices

A 3D-printed data sculpture that abstractlyd displays average price per square foot for housing in the San Francisco area.


Physicality: 3D-printed plastic

Architecture: non, ~12″ tall

Interaction: None, static

Pros: Form takes on powerful metaphor of ripping apart; content well-researched and clearly discerned from sculpture; excellent craftsmanship; process well-documented

Cons: No sense of data scale; lack of relation to human body or architecture

Rules for Animated Infographics


Information Animated Infographics
Editors T. Finke & S Manger (2012)

“Well-made animated information graphics are based on clear decisions about what matters and what should be left out.” – Stefan Fichtel (in Finke & Manger, 8)

“By comparing different data sets and visualizations of the data and embedding them in a context, the view sees the result in the form of a narration with the help of illustrations” (Finke & Manger, 21).

The Pros and Cons of “passive, animated information graphics that have a linear structure:”





In sculptural, interactive works…

Time Sequences
…if time is represented, interactivity may permit atemporality.

Directing the Viewer
…the viewer cannot experience events in a predetermined order.

Changing Perspective
…emphasis should not be encoded in perspective.

Viewing Time
…the viewer is permitted to spend as much time as needed (or desired) for perception of content.

…the information presented may be perceived in various orders, and will permit different outcomes depending on the viewer.

…the statistical content must balance between rich and generalized visualizations, understanding experience can cease upon exhaust of attention.

…the viewer is permitted to ask questions or examine the data in detail.


Combinations of Visualization Techniques in Animation:

Schematic Diagrams
A way to view structure of an object, connections (of objects), or abstract processes (temporal connections of objects). Drawings of the object should be only as detailed as necessary to communicate understanding. Cross sections should be carefully cut (and visualized) so that inside and outside distinctions can be made and the form as as whole is still readily perceived. In charts of process, if the process is abstract, consider employing visuals that offer interest-piquing metaphor.

When making process graphics, it is helpful to recognize an overall image, a sequence of images, and the feature graphic. The overall image should lead the eye through the whole, often helpful to read top-left to bottom-right. Any visualization of the process must be distinct from the elements or actors, as such the elements and actors must be perceptually grouped/organized to show relationships. Feature graphics or elements must be introduced early in sequences, so that the rest of the sequence can animate the process and relationships.

Cartographic information pertaining to event space should be placed in context, with appropriate amounts of labels for bordering lands or geographic features (like bodies of water). Thematic maps provide a spatial distribution of one or more phenomena; in these cases geographic data is linked to statistical data. Codifying the map with symbols or iconography is often necessary, but in the course of an animation the legend should not be present the entire time (labels or voice-over work can suffice), so clear metaphors for visual encoding must be established. Moving images of maps need not a title, because tracking and eye back and forth from title to map (or legend to map) costs time.

“A good information graphic makes its content, or its essence, as accessible as possible in a brief period of time” (Finke & Manger, 109).


Process & Pitfalls: Writing in InfoVis

Process and Pitfalls in Writing Information Visualization Research Papers
Tamara Munzner (2008)

Applied Reading 1

Patrick J. O’Donnel

Munzner begins her meta-research paper, or model paper, supported by her involvement as Posters and Papers Chair of the IEEE Symposium on Information Visualization, by recognizing common pitfalls witnessed in research writing for the information visualization community.

“A good way to begin a research project is consider where you want it to end” (Munzner, 2). This advice, as logical as it may sound, gives a false sense of applicability with its proverb-like brevity. It is my interpretation that Munzner wishes to espouses is one of a researcher’s awareness of a sound argument during the project’s conception. If taken too literally, one could bias any creative effort to eschew undesired form. Instead, she most likely supports her later categorizations of papers as having validation methods unique unto themselves. Breaking ground on a new research topic without these validation methods in mind could prove fruitless, despite richness of content and discovery.

Non-Exclusive Categories of Research Papers

(1) Technique Paper

The main contribution of a technique paper is a novel algorithm or implementation. The validation methods are beyond the scope of my thesis work at this time.

(2) Design Study

New visual representations in context of a problem are the contributions of Design Studies. In order to accurately justify the visual encodings utilized, one must include brief and relevant contextual history of the problem as well as any requirements obtained through task analysis, so that the appropriateness of the solution can be appraised. Furthermore, a researcher can also conduct and include case studies, scenarios of use, or evidence of adoption by a target audience to help support their solution’s approach. This style of paper is well within my personal technical abilities and theoretical scope for my thesis.

(3) Systems Paper

A Systems Paper evaluates the use of infrastructure, framework or toolkits in software or applications. These types of papers consider choices in structure rather than visual encodings. These types of papers are not within the scope of my abilities to author with my current thesis.

(4) Evaluation Paper

Information Visualization systems and techniques are examined in use by some target population in any Evaluation Paper. Both laboratory studies of abstracted tests, and real-world behavioral field studies fall under the umbrella of this category of research paper. The lines between Evaluation Papers, Design Studies, and Ethnography can be blurry and often co-exist. This style of research is within my capabilities, but does not exclusively match the creation-of-works approach of my thesis.

(5) Model (Meta-Research) Paper

A Model Paper is considered a Meta-Research Paper because it presents formalisms and abstractions about the nature of work, production, and process. Taxonomy models seek to detail the space of some topic (such as categorization of other works). A Formalism model provides new terminology and methods by which to analyze past (and future) works. Commentary models craft an argument for a position relating to the field, much like an opinion column or advice but supported by observation, reflection and prediction. Some parts of my thesis will likely lean towards a Formalism Model paper, as it will detail my conceptual model for working with material, space, and interaction simultaneously.

Pitfalls in writing research papers come in many forms during all stages of researching and writing. Munzner suggests that many researchers fail to connect their contributions to either technique (algorithmic) or design. In a well-drafted design study paper, a well-versed information visualization professional must know how to “clearly state the problem” that can be addressed through visualization techniques, know those very techniques, and justify the technique used against other techniques in existence. When writing a paper that exists in more than one of these categories, understand which category is guiding your writing structure most, and which categories are secondary—and how to properly embed them not to distract from the primary purpose.

Justifying visual encoding and interaction methods is a necessary consideration for design study papers; do not skip discussing task analysis. Similarly, any kind of technique proposed that does not discuss who or when it might be used is hardly useful. Specificity of use case is not a requirement, but at least abstractions of tasks in domains is advised to be included in research documentation.

Visualizations in three-dimensions are often necessary when the mental model of the content must be mapped less abstractly to afford quick understanding.  When working with 3D spatial data, consider occlusion and interactivity that permits navigation of perspective. But do not assume this to be solved, as human memory is limited to make judgments from a current viewpoint to a previous viewpoint.

Research papers should not read like a manual or a journal entry; they are not exhaustive of your process, rather they are tailored and designed to make an argument. The scope of your research (and thus paper) should be self-contained and not so dense as to cover too many topics. A proper research paper should present the amount of material necessary to make your point and be able to be reproduced. To avoid missing details or including unnecessary details, consider using a sentence such as “My contribution is…” near the end of the Introduction and ensure your writings address that contribution thoroughly.

“What can we do that wasn’t possible before? How can we do something better than before? What do we know that was unknown or unclear before?” (Munzner, 12).

Convince the reader of your paper that your contributions are unique by detailing how your work differs from the established work of the intellectual community past and present. Do not simply cite previous work, explain in what ways does it not solve the problem you’ve identified. Consider grouping previous works into categories to systematically carry out analysis of each work and it’s limitations. No assertion should go unattributed. If a fact is presented as justification and no source is cited (such as “general knowledge” or “conventional wisdom”) consider deleting it, making a different justification, or searching for research on that topic. Research papers that fail to disclose reflection on their own weaknesses, limitations, or implications are seen as unfinished.

When comparing your results to other work, compare with the most up-to-date work possible. Choosing data sets to test with use-cases should be indicative of the data sets actual users would come across. Tasks used to epitomize results should be justified, in that actual users would come across the need for this procedure. Cherry-picking tasks that showcase your solutions strengths (or worse, hides its weaknesses) dilutes your results with bias.

Writing a research paper requires a calculated style that aims to produce understanding in the audience. It is often helpful to present solution descriptions in the order of what it is, why you chose it, and then how it satisfies the problem. Captions should be written in full-sentence, paragraph form so that a chart, diagram, or image could justifiably stand alone, and flipping through the paper would allow an overview via the images only. When comparing visual techniques to others, it is helpful to do so side-by-side, rather than relying on the capacity of human memory.

Glasses: This Object and its Origin

Objects exist in multiplicity.

The physicality of this specific pair of glasses is just one perspective in defining these glasses.

these are my glasses

From where did these glasses come? Of what materials are these glasses crafted? What parts of these glasses are unique to myself? What important milestones have these glasses passed? Where and when do these glasses get used (or not used)? How do these glasses effect my life (physically, emotionally, etc)?

From where did these glasses come?

These glasses were ordered on Zenni Optical‘s website.

Zenni Optical began in 2003 in the San Francisco Bay Area. They boast more than 6,000 styles of frames online, including men’s/women’s/kid’s frames and lenses, as well as sunglasses and sportswear glasses. Zenni owns at 248,000 sq. foot facility that “houses state-of-the-art Rx and Edging Labs.” While the pictures show the San Francisco offices, the manufacturing plant is located in China (according to the Terms of Use), and most US orders are made in China, shipped to San Francisco, then to your desired location.

Of what materials are these glasses crafted?

These frames are specified as Browline Sunglasses #732021

the specifications for my frames

Browline Sunglasses #732021 are made from a mixture of acetate (Cellulose acetate) and silver alloy full rim and silicone nose pieces. The lenses are made of 1.61 High Index plastic,  though no specific plastics are specified over 1.58 refractive indexes. There is an anti-reflective coating on them to reduce glare that is of unknown/non-specific composition.

What parts of these glasses are unique to myself?

The prescription: I have myopia, or nearsightedness, in that I can’t see at distances well, but reading-length vision is appropriate–indicated by the negative sphere (SPH) lens power. (I also have a slight myopic astigmatism in my right eye).


PD stands for pupillary distance, or the distance between the pupils. According to an infographic on Zenni Optical’s website, adult PDs usually fall between 54mm-74mm.

The lenses are often dirty, as I only clean them with cotton part of a shirt I am currently wearing. The frames are not level with the table, as I do not adjust them to uniquely fit my ear and nose-bridge shape.

What important milestones have these glasses passed?

I broke my previous pair of glasses on July 10th, 2015 at approximately 1:15am. I took them off while sitting on a front porch in the Short North of Columbus, Ohio, and a friend stepped on them.

I ordered these glasses on Dec 12, 2015. They arrived Dec 21, 2015. 12 of 15 selfies I’ve taken since Dec 21, 2015 have been while wearing these glasses. I’ve now owned them for 56 days.

Where and when do these glasses get used (or not used)? 

I wear these glasses most days. I also have contact lenses which I wear on occasion. I normally only wear contact during sports with physical interaction (like volleyball) or when I plan on running long distances (sweating a lot).

When I put on my glasses in the morning, I grab them from the top (or second to top) shelf on my bedside table. I usually set them next to my iPhone while it is charging, a glass of water, and my keys and wallet. I wear them while commuting and while in class. I often wear them while at the gym but find myself taking them off when doing some ab exercises on the ground. I take them off to shower at home, and I place them next to the hand soap dispenser on the left side of the sink.

How do these glasses effect my life (physically, emotionally, etc)?

Physically these glasses are a hassle when wearing them in the rain. I commute using public transit and I’ve only worn them once in the rain. They also leave a slight impression on the bridge of my nose from wearing them on a daily basis.

impression of the silicone nose pad after daily wear

I originally bought the glasses because of the 1960s academic style, epitomized by Henry Crane (portrayed by Rich Sommer) in AMC’s MadMen. I think of glasses as an essential part of my personal style. This particular style emphasizes a brow line that I personally think is weak compared to other’s brow lines.

Rich Sommer as Henry Crane in AMC’s MadMen, styled by Janie Bryant


Research Methods: Readings II

“Why Should Engineers and Scientists Be Worried About Color?” Link
Bernice E. Rogowitz and Lloyd A. Treinish

the same data but mapped with mathematically equivalent scales, but one adds a threshold of significance (sea-level)

With the color map on the left, elevation is a continuous variable. However, its corresponding color scale ranges among approximately 5 discrete color categories. This confuses the reader.

“One result of this work has been a set of colormaps which take into account the data type, the spatial frequency of the data, and properties of the human perceptual system.  These colormaps are all designed to create more faithful impressions of the structure in the data.”

Data types include:

  • Nominal (no mathematical relationship)
  • Ordinal (occur in an order, but no mathematical relationship)
  • Interval (experimentally determined relationships)
  • Ratio (equal measurement between values, with zero included)

How do we choose color for these data types, so that our perception of color judgement matches the comparison of the data types?

Hue, Saturation, and Luminance: three perceivable dimensions of color

Hue, by itself, is not known for producing accurate judgments of a coded variable with varying magnitude. How to choose between a saturation-based color scale or luminance-based one? If there are great frequency shifts, use saturation-based color scale to see the graduation of changes. If there are small frequency shifts, use luminance-based color scale to emphasize distinctness in extremes.

Two special cases for color ranges: Segmentation and Highlighting

  • “In segmentation, the analyst’s goal is to look at the whole range of data, but partitioned.  If the segments are derived from interval or ratio data, it is important to preserve the perception of order, that is, that the order of the segments matches the order of the data values.”
  • “In highlighting, the analyst’s goal is to focus on a limited range in a variable and study how this range expresses itself in the data set.  The analyst, for example, may want to probe the exact ranges where the dose of a radiological treatment affects distant healthy tissue, or the particular magnitude at which the wind changes direction in a meteorological simulation.”
four color maps of photochemical pollution levels with a rainbow-scale (top-left), a isomorphic color-scale (top-right), segmented color-scale (bottom-left), and a highlighting color-scale (bottom-right)

So why the three other color scales? Firstly, an isomorphic color mapping has equal perceptual changes in color between equal intervals of the data. This is the “most” truthful.

Let’s say an alternate analysis is needed (maybe even quickly), a segmented map could show dangerous areas. In the bottom-left map, maybe 140 and above are toxic levels of chemicals. They are easily picked out of the map. What about a specific area, like low levels of a chemical that needs to be evenly spread throughout an area? The lower-right map shows off areas lower than 50 with perceptual ease. The higher areas, sufficient in chemical concentration, are not distinguished between.


“Visual Math Gone Wrong” Link
Robert Kosara

from the US Census Data Visualization Gallery

So what’s going on here? We have some population arithmetic. Important statistics, but what’s going on visually? Area arithmetic: something perceptually is four times as hard to grasp as single dimensional arithmetic. (And outlines for negative population double coded with the subtraction symbol. A good effort, fill would have been better without an outline, maybe on a toned background. But just use a bar chart since population is only a single dimension.)

Where do bar chart comparisons fail? Only once you get to vastly different scales (near 50x-100x difference between minimum and maximum values). Otherwise, comparisons among column components as well as cross-column comparisons are possible.


Ch 6: Visualizing for the Mind from The Functional Art
Alberto Cairo

“The ability to anticipate what the brain wants to do can greatly improve your information graphics and visualizations.” —PREATTENTIVE FEATURES

The detection of object boundaries is based off of variations of light intensity and color, and on how well the edges of the things you see are defined.

The brain is much better at quickly detecting variations in shade than in shape.

notice how color effects the visibility and ease-of-search when iconography is plentiful and too similar

Gestalt School of Thought preaches that the brain can recognize and sort differences in patterns because conscious thought can catch up with it. Examples include proximity, similarity, connectedness, and closure.

Cleveland and McGill (at Bell Labs 1984) published a groundbreaking study that pitted visualization methods against data perception accuracy. Most notably, position along common scale (single dimension with same starting point) and position along non-aligned scale (single dimension with same scale but different baselines) allowed accurate judgements. However, estimations in color saturation, color shading, and curvature were the least accurate.

10 vs 7 comparisons in terms of single-dimension, circular area, and hue

Stereoscopic depth perception (the difference between left eye and right eye images) allows humans to see in 3D however, there are monocular cues that also assist in 3D vision, including saccades, shadows, relative size, and detail/horizon blur.

“Color Use Guidelines for Mapping and Visualization”
Cynthia A. Brewer


One-Variable Color Schemes

Qualitative Schemes: categorical, no computational relationship between states

  • when using color between categorical data, distinguish them with differences in hue, and slight differences in lightness… not equal lightness. (Why? the physiological system to distinguish hue has poor shape- and edge-detection, the lightness difference will clarify boundaries.)
  • the more categories (the closer your hues), the greater the difference in lightness needs to be. also, consider why you’re displaying that many categories.
  • if any area is small by comparison to other areas its spatially proximal, a greater contrast in lightness would benefit detection.

Binary Schemes: on- or off-states, yes- or no-states

  • differences in hue and/or lightness can be used equally effectively.

Sequential Schemes: ordered, low- to high-values

  • mapping low values and high values depend on the display. treat the display or background default as low, and the addition of ink or light (etc) as an increase.
  • pure black-and-white schemes will have a disadvantage when it comes to the default of the display (areas with no data, like water on a country map) will appear to be on the sequential scale as a zero point.
  • it is not recommended to vary a sequential scheme by saturation only when there are more than 3 sequenced points in your range
  • if using more than one color in a sequential scheme, vary lightness and darkness singularly and evenly, despite hue.
  • full-spectrum schemes (rainbows) are perceptually disadvantageous because yellow is perceptually lighter in hue, and darkened yellow is perceptually desaturated, leading to misperceiving information where, often, none exists.

Diverging Schemes: ordered, with a noteworthy midpoint (or similarly critical point)

  • recommended to use two hues and darken them as their absolute value moves away from the critical point.

Two-Variable Color Schemes

Qualitative vs Binary Schemes

  • choose two hues (one for each binary) and vary lightness by qualitative values
  • increased saturation on the binary value you wish to emphasize

Qualitative vs. Sequential Schemes

  • choose three hues for the qualitative, and vary lightness by sequential values

Sequential vs. Sequential Schemes

  • a logical mixture of two hues and a lightness. lightest represents low sequence in both variables; increased hue and lightness in each color paired with each sequential schemes; increased hue combines in both to show high sequence in both variables.

Balance Schemes

  • neither end of a balance scheme should be emphasized, choose hues carefully to match saturation as best as possible, and vary hue equally between the domain.
  • a special case of sequential/sequential scheme, but one variable increases as the other decreases and vice-versa: they cannot diverge from this formula.

Diverging vs. Diverging Schemescolor_schemes_diverge.png


Plot and ggplot2 with R-Studio

Data from Vision Problems in the U.S. provides estimates of the prevalence of eye-disorders in the US by state in adults 40 and older.

Here is the initial outputs of my work with R-Studio statistical software:

  1. When plot() is envoked on R-Studio, a matrix of plots are established by header columns. This particular function ran very slow, so I limited the data plotted to only entries from state: “OHIO”. Most noticeably, my values for vp (vision problem), age, race and sex are all categorical.
  2. I decided to further install the ggplot2 library for some more customizable plots. The color graph plots age against rate, with color determined by vp (vision problem). Each of my categorical variables has a “total/all” section that is not separated out from the individual state, race, gender or age data.
  3. I then attempted to use the box plot feature, which did not yield any additional insights.

Further steps to clearly visualize this data will address these problems:

  • What strategies are best to see averages for “all” categorical data alongside individual categorical data (e.g. female, or white, or 55-64 yrs)?
  • How can multiple categorical variables be presented at the same time (40-50yr Hispanic male vs. 51-60yr Black female vs. etc.)? Shapes, colors, other?
  • Should the data be presented as exploratory or tailored to meet a specific idea or perspective?
  • Which of these diseases/disorders result in a prescription for eyeglasses or vision correction?

GLASSES \ data

Behavioral Risk Factors – Vision & Eye Health

Centers for Disease Control and Prevention

“In 2013 and subsequently, one question in the core of BRFSS asks about vision: Are you blind or do you have serious difficulty seeing, even when wearing glasses? From 2005-2011 the BRFSS employed a ten question vision module regarding vision impairment, access and utilization of eye care, and self-reported eye diseases. The Vision and Eye Health Surveillance System is intended to provide population estimates of vision loss function, eye diseases, health disparities, as well as barriers and facilitators to access to vision and eye care.”

Prevalence and Distribution of Corrective Lenses among School-Age Children

“In the 1998 MEPS, 23.9% of the 5,141 children aged 6 to 18 years had corrective lenses. When weighted to the U.S. population, an estimated 25.4% (95% confidence interval, 23.8 to 27.0%) of the 52.6 million children aged 6 to 18 years had corrective lenses.”

Original data source (SAS or ASCII)


Prevalence of Adult Vision Impairment and Age-Related Eye Disease in America

“The Vision Problems in the U.S. report and database provides useful estimates of the prevalence of sight-threatening eye diseases in Americans age 40 and older. This report includes information on the prevalence of blindness and vision impairment, significant refractive error, and the four leading eye diseases affecting older Americans: age-related macular degeneration, cataract, diabetic retinopathy and glaucoma. The estimates in this report use published prevalence rates and 2010 U.S. census data. These estimates reflect the growth and changing racial, ethnic and age composition of the United States population.”