Category: visuals

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visuals

Some notes

A few comments:

I’ve passed my third and final candidacy exam! Now, on to proposing a research project. I’ll certainly be talking more about that in the upcoming weeks…

Today, I’ve added some portfolio items to this site. There’s also now a new “my portfolio” tab at the top. This includes some science visualizations, web-based projects, and excerpts from a few course papers. This has all been on another site up till this point, and I figured I should get it all in one place. The issue with some of the materials is that they’re pretty large visuals, so I’m trying to think of the best way to include it here. I’m a bit limited by the WordPress template, and will have to put some more effort into figuring out the best way to present this sort of material.

I’ll be posting in the next few days about a semi-pilot (if that’s a real term) study on interactive science visualizations that I did this semester. What I wanted to look at was whether a specific type of interactivity in phylogenetic trees helps people learn relationships better than simply looking at a non-interactive diagram. More on that soon.

Also, look for a special Friday bunnyblogging gift guide this week, for that special rabbit in your life!

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discourse community/community of practice exam readings information representation visuals

Exam readings: diagrams as boundary objects

For today, two takes on the concept of “boundary objects:” concepts, texts, machines, diagrams, etc. that serve as meeting points between different social worlds.These focus on diagrams (natch): infrastructure schematics and Gantt charts.

Lucy Suchman. “Embodied Practices of Engineering Work.” Mind, Culture, and Activity 7(1&2): 4–18, 2000.

Summary: Uses ethnomethodology (EM) and activity theory (AT; doesn’t use the triangle) to describe design practices in civil engineering. Her focus is the use of CAD and paper diagrams in planning; these diagrams connect EM & AT. EM is phenomenological & descriptive of artifacts in use and work practices; it’s not used to build generalizable theory. AT focuses on how tools mediate and are in turn created by social work practices; it’s also ultimately not generalizable b/c of its focus on specific situations (framework, not theory). Her research comes from conversations with/tutorial of the process of designing a road by an engineer. The CAD display is complex: 2-D and 3-D views, puts plans onto 3-D topographical layer than lets engineers take viewing sections through it, and includes natural and built infrastructural features (old infrastructure, new project, and temporary elements needed to support construction). Engineers also use paper: maps (taking collective notes, getting sense of big picture) and notes. Two key practices bring together these elements: “professional vision” (mental simulation of the project site, as aided by the CAD tools), and embodiment of engineers (gestures, hand motions to indicate third dimension, etc.). Paper and CAD have different affordances, so engineers use both. Concludes by describing similarities/differences between EM and AT.

Comments: This paper touched on AT, but was not strictly an AT analysis (more an EM-based description). Point seems to have been to use her case study as a way to draw parallels between the two methodologies.

Links to: Roth (AT description); Sharples et al. (more standard? AT analysis)

Elaine K. Yakura. “Timelines as Temporal Boundary Objects.” The Academy of Management Journal. 45(5): 956-970, 2002.

Summary: Yakura looks at timelines (Gantt charts) in work environments as “temporal boundary objects:” they render time concrete and serve as points of synthesis and negotiation among different groups in a business (e.g., programmers, managers, clients). They also embody elements of narrative (beginning, middle, end) that helps people envision milestones as well as project completion. They are “monotemporal” (mechanistic & standardized view of time), in contrast to “pluritemporal” (multiple cultural/occupational groups mark time with different activities), and serve as sites of negotiation and translation among different groups. Three functions of timelines are for scheduling, synchronization, and time allocation for various tasks; these categories are not interpreted the same by all groups involved in a project, so the timeline is a site of discussion. Presents a case study of timeline use, discussion, and renegotiation (as unforeseen events required updating it); the case study illustrates pluritemporalism & use as a boundary object.

Comments: Example of a visualization as a boundary object between different groups. Timelines aren’t intended as permanent artifacts, but Yakura points out that they’re treated as reality even while undergoing revision; they also symbolize a tangible work product between milestones/when tasks are in process.

Links to: Suchman (paper maps as boundary objects in engineering)

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discourse community/community of practice exam readings learning theory visuals

Exam readings: using visuals to understand science

More on the use of diagrams in understanding science. First, a paper which suggests that a key process of science education is a process of learning how to take observations, make diagrams (or other descriptions), and then communicate about those diagrams with other people. This is a relatively simple concept, but one which is often not emphasized in science education (at least, it’s not emphasized how these skills will help students learn science. The second paper is tangentially connected to this idea. It’s about the challenges in incorporating data visualization tools into community science projects- tools that many scientists have no trouble interpreting, but that members of the public do.

Wolff-Michael Roth and Michelle K. McGinn. “Inscriptions: Toward a Theory of Representing as Social Practice.” Review of Educational Research. 68(1): 35-59, 1998.

Summary: The authors use the concept of inscriptions (=physical graphical displays; distinct from mental representations) to argue for a social, rather than purely individually cognitive, view of activity. Their focus is on emphasizing the conscious consideration of inscription-creating practices during science learning; I’m skipping the discussion of pedagogy/classroom practice. Inscriptions are used in several ways in discussions: talked about, talked over (e.g., used as backgrounds), serve as boundary objects for discussion among different groups, have rhetorical functions (demonstrative), and serve as pedagogical devices. Inscriptions are materially embodied signs: mobile (immutable while moving); can be incorporated into different contexts, rescaled, combined, reproduced easily; can be merged with geometry (i.e., mathematicized/ gridded); and can be “translated” into other inscriptions. The relationship between inscription and inscribed is traditionally thought of as correspondence or “truth;” current thought is that inscriptions are a result of distinct social practice, so distinct from the thing inscribed. Inscriptions’ creation practices determine whether they’ll be accepted by a community; this is grounded in social practice and suggests that inscriptions can’t be properly interpreted outside the context of their use. Also discuss their use as boundary objects with different functions in face-to-face vs. dispersed settings (though they mention that networked presentation tools are allowing a fuller range of discussion using inscriptions among dispersed groups).

Comments: Focus is on formal education environments and framing science practice as a series of creating, interpreting, and sharing inscriptions. Their background discussion helps tie together some of my other readings on communities of participation, distributed cognition, and visualizations.
Links to: various things…

Stephanie Thompson and Rick Bonney. “Evaluating the Impact of Participation in an On-line Citizen Science Project: A Mixed-methods approach.” in J. Trant and D. Bearman (eds.) Museums and the Web 2007: Proceedings, Toronto: Archives & Museum Informatics, published March 1, 2007.

Summary: Report on assessment of participant use of eBird, Cornell Lab of Ornithology online bird sighting tracking software. In eBird, participants enter information about their bird sightings either from a list or on a map; this data is then pooled with other observations. Users can use several tools for data visualization of all bird observations, either selecting one species to focus on or selecting all observations from a particular area. Tools include maps and various types of charts. This project has educational goals, but in entirely self-instructed and –directed (instructions and a FAQ are available). In 2005, CLO conducted a new user survey, which surveyed users on registration and again eight weeks later; this included a standard demographic questionnaire, an assessment of users’ understanding of the “View and Explore Data” tools, and a “Personal Meaning Mapping” about conservation (a short-answer assessment approach). For the data analysis tools, they found that most users who responded didn’t select the correct tools to answer the question asked. In addition, many people didn’t answer this question, probably because they hadn’t used or weren’t comfortable with these tools. The authors suggest that more active instruction in how to use the tools is probably needed.

Comments: This paper mainly presents an example of the challenge in incorporating data visualization tools into an informal learning setting.

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exam readings information representation visuals

Exam reading: “Visual explanations”

This second book by Tufte is probably more applicable to the narrative study of images (though now I’m wishing I’d put “Understanding Comics” on my reading list).

Edward Tufte. Visual Explanations: Images and Quantities, Evidence and Narrative. Cheshire, CT: Graphics Press, 1997.

Summary: This book focuses on strategies for presenting information about change: motion, process, cause/effect. Quantities can be represented by labels, encodings (e.g., color-coding), and self-representing scales (e.g., penny in a photo); maps do this by location on grid & size of marker. Creators should place data in appropriate context to assess cause/effect, make quant. comparisons, consider alternative explanations, and assess potential errors in numbers. “Numbers become evidence by being in relation to” other numbers, objects, etc. change can be inferred from multiple, layered views (incorporates parallelism of space or time, lets viewer make comparisons). Discusses principle of “smallest effective difference”- make all distinctions as subtle as possible, but still visible. Also “disinformation design:” suppressing content and preventing reflective analysis by “visual masking” of important features with unimportant ones (e.g., cigarette warning labels). This is not necessarily intentional: can occur through faulty parallelism, trying to emphasize everything, or false clusters created by proximity. Ends by discussing complex narrative forms of data display, or “confections.” These juxtapose tangentially related visual elements in collage fashion; he emphasizes that a purposeful arrangement of these renders them meaningful (in contrast to just slapping them together because).

Comments: Tufte discuses magic diagrams as ways to show action sequences and time; comics do similar things. He briefly discusses the design of customizable computer interfaces as an example of visual narrative (one example used is dynamic museum guides). He applies his standard design ideas (high information-rich content, make clear & sufficient computer commands visible)- I wonder if that last suggestion will change as more people get used to usingapps on wireless devices with few controls?

Links to: Kostelnick & Hassett (discuss the social context of design, rather than design principles); Nersessian, Gilbert (cognition & visuals)

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exam readings information representation transparency visuals

Exam reading: “Visual display of quantitative info”

For a “traditional” (i.e., not community- or critical theory-based) approach to design of graphics, I’m including two books by Edward Tufte on my reading list. There’s a certain set of information visualization people that love his work, but a set of critical theorists and rhetoricians that regards it as arhetorical and emphasizing words (and data) over visual elements. Anyway, here’s the first book on my list:

Edward Tufte. The Visual Display of Quantitative Information, 2nd ed. Cheshire, CT: Graphics Press, 2001.

Summary: Tufte views infographics as “paragraphs about data;” however, design is universal- like mathematics rather than language. Graphics reveal data at several levels (overview to fine-grained), should be transparent, avoid distorting data, be information-dense, encourage comparisons, and be closely integrated with text, statistics, and datasets. Tufte briefly discusses the history and various types of graphics (data maps, time-series, “space-time narrative,” & relational graphics). Has chapters dedicated to graphical integrity (e.g., avoid distortions of area or scale, provide context), “data-ink” ratio=”data-ink”/total ink used to print graphic (higher better) and “chartjunk”-decorative features that don’t add interpretive info. Graphical elements should serve >1 function (e.g., position, size, color, and shape of data points can all reveal different dimensions). Also discusses data density= number of entries in data matrix/area of data graphic – idea is to try to maximize data density (maps as example of type with high data density); graphics can be smaller than we may think. Likes “small multiples”: multiple small graphics with the same format, but providing comparisons bet. changing variables (likens these to movie frames). Graphical elegance=simple design + complex data. Discusses appropriate uses of words to tables to graphics.

Comments: Outlines several reasons for continued problems with graphics: lack of quantitative training for artists, idea that statistical data are boring, idea that graphics are unsophisticated. Ideas that graphics should be transparent and conventions are universal don’t fit with rhetoric of design (though does recognize deliberate “distortion” of data as rhetorical decision). He gives several ideas for simplifying/modifying current forms; assumes people will accept these if they see them enough (resistence to new formats can be easily overcome by designers).

Links to: Kostelnick & Hassett (rhetorical design); Tversky (different emphasis on maps as data viz)

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visuals

Quick post…

I’ll be giving a talk on Friday at a panel about using visual media to promote sustainability, here at UCF.

I would have posted this over the weekend, but I spent the entire time basically glued to the computer working on my 2nd candidacy exam. Which I am told I just passed 🙂

Here’s the relevant info:

PANEL PRESENTATION: Fostering Sustainability Education through Film and Photography

Exploring the Use of Film to Inform and Persuade in the Area of Environmental Ethics
Stephen M. Fiore, Brittany C. Sellers, and Elizabeth K. Phillips
Department of Philosophy (SM) and Department of Psychology (BS, EP)

Using Photography and Flagship Species to Promote Conservation
Sonia H. Stephens
Department of English

3:30pm to 5:00pm * Friday, November 12th * 2010
ROOM PSY 226 * Department of Philosophy, Psychology Building

Sponsored by: Department of Philosophy Ethics Center Initiative and the Center for Humanities and Digital Research Digital Narrative Group

This panel presents two unique projects at UCF united in their attempts to understand attitudes towards the environment and how media influences these attitudes. The first presentation describes a program of research and education centered on using a blend of film and socio-cognitive theory to impact personal change related to environmental ethics. The overarching goal of our research is to understand how documentary films can inform individuals about environmental issues and the degree to which they lead to attitude change, taking into account individual time perspectives. As such, we link research in the cognitive and learning sciences with the use of story and film from the humanities. Implications for this research include furthering our understanding of the role of narrative film in influencing behavior and, more broadly, the development of socio-cognitive theory on how narrative can aid in behavior modification via attitude change in the area of environmental ethics.

Our second presentation focuses on the ways that photography is used in the conservation movement to create personal connections between people and threatened species. Photography can be used rationally to document ecological changes, but it is even more powerful when used to make emotional or ethical arguments for conservation. Photos are effective rhetorical tools because they mediate between our inner & outer realities, helping us reconcile what is with what we think should be. One way the conservation movement uses photography is to bring public awareness to “flagship species-” charismatic species that call attention to larger conservation issues. This presentation explores the rhetorical choices made by conservation organizations in selecting which species to focus on, how photos are formatted, and what types of arguments these photographs ultimately make.

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exam readings learning theory visuals

Exam reading: “Ins and outs of learning”

This chapter covers current ideas on how memory works and also why visuals are effective for learning:

David N. Rapp and Christopher A. Kurby. “The ‘Ins’ and ‘Outs’ of Learning: Internal Representations and External Visualizations.” In John K. Gilbert, Miriam Reiner, and Mary Nakhleh (eds.) Visualization: Theory and Practice in Science Education, pp. 29-52. Dordrecht: Springer, 2008.

Summary: This chapter primarily discusses how people learn from visualizations (structure of memory); also provides suggestions for applying research in this area to teaching. Cognitive science & learning research suggests a few things about learning, e.g., external models should match what we want people to remember, and info that’s too abstract may be difficult to apply in specific situations. They discuss three categories of internal representations: visual memory (short-term & long-term recall), visual images (internally-generated & often speculative), and knowledge representations (most complex, focus is on causes and motivations of simulations rather than on just the images.) Sci. viz. should aim to affect viewers’ knowledge representations, and through them, higher-order concepts & processes. They take a “perceptual” view of memory (idea that concepts are linked to the sensory mode by which they’re learned; embodied cognition), as opposed to an “amodal” view (memory concepts aren’t systematically related to real-world experience.) Two models for learning suggest that the mode of learning will influence how memories are represented and how they’re ultimately recalled: “dual-coding” (memories are either verbal or visual; more complex concepts are harder to render visually, so harder to recall) and the “working memory” model (working memory contains acoustic and visuospatial components; relying solely on one or the other can overload the system and lead to poor recall.) The authors suggest that these two models help create a rationale for incorporating multimodal (including visual) components for learning.

Comments: Basically, this chapter provides support for the idea that multimedia (including touch) will create better learning outcomes (though they do touch on the question of whether concepts learned in one mode will transfer to others.) Interpretation of visuals is based on prior knowledge (scaffolding)- cultural aspects are important- this makes analogy & use of conventions helpful. They include touch and sound as well as images in their idea of “visualizations” (basically, like multisensory modalities.)

Links to: Lave & Wenger (not as social as L&W, but some social stuff here); Zhang & Norman (discuss process of having external & internal representations converge, but not explicitly distributed cog.); Burnett (core list; cognition & image-worlds)

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exam readings information representation science studies visuals

Exam reading: “Framework for visual science”

I’m jumping from a cognitive science approach to visuals back to a more social & rhetorical approach with this chapter. Like my last two readings, this one provides yet another framework for analyzing scientific visuals, but the approach is pretty different (which is great, because I feel like I really need a break from the framework stuff at the moment.)

Also, I believe this is one of the longest titles in one of my readings…

Luc Pauwels. “A Theoretical Framework for Assessing Visual Representational Practices in Knowledge Building and Science Communications.” in Luc. Pauwels (ed) Visual Cultures of Science: Rethinking Representational Practices in Knowledge Building and Science, pp. 1-25. Hanover: Dartmouth College Press, 2006.

Summary: Pauwels’ aim is to establish a framework for analyzing scientific visualizations that includes: the nature of the referent, type of medium, methodology for creation, and uses of the resulting image. The nature of scientific referents falls on a continuum from material/physical to mental/conceptual: directly observable, visible with tools, non-visual phenomena, explanations of non-visual data trends, postulated phenomena and metaphors. Representations can include multiple types of referents (e.g., photo with arrows for non-visual process), and each representation expresses a reality that shapes the image’s interpretation. Illustrations should be both representative of their subject matter and valid examples of the subject (e.g., a photo of a specific bird vs. a stylized drawing of that species.) Production processes all have intertwined social, technological, and cultural aspects (affordances, conventions, and constraints.) Different referents will have “appropriate” conventions for presentation; conventions also vary with the purpose of the illustration (further analysis, teach concepts, etc.) The upshot is that representations have multiple purposes/motivations and may be interpreted differently (e.g., can be used as boundary objects.)

Comments: Scientific illustrations are less a transparent “window” than a carefully selected and stylized rhetorical presentation (though P. doesn’t use “rhetoric”.) Discusses the need for greater awareness of all aspects of his framework for scientific illustrators (and also public)- e.g., awareness of implications of disciplinary conventions for image format. Physical representations are inherently social objects, unlike mental representations. Visual media have one important constraint- that they depict a specific example, rather than words, which can specify a range (e.g., a specific drawing of a flower vs. “this flower has 6-8 petals”)- the viewer has to decide how significant each element of the illustration is (if they even have the awareness to judge this.) Verbal descriptions or use of conventions can help with this problem.

Links to: Kostelnick & Hassett (conventions & rhetorical uses of images); Gilbert (categories of scientific illustrations)

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exam readings learning theory visuals

Exam readings: Using visualizations in science education

These two readings are from the literature on science education, about the importance of visualizations for science. These two authors focus on different topics in the broad area of visualizations and science education.

Barbara Tversky. “Prolegomenon to Scientific Visualizations.” in John K. Gilbert (ed.) Visualization in Science Education, pp 29-42. Dordrecht: Springer, 2005.

Summary: Tversky uses the analogy of scientific visualizations (and viz in general) as maps to aid understanding. Effective maps select important information and even distort it for emphasis (schematize it); abstract relationships are often thought of in spatial terms (e.g., good=up), and this mapping seems to hold meaning/be non-arbitrary. While maps are composed of elements (icons + morphograms [simple schematic shapes that are vocabulary-like: lines, arrows, etc.]) and the spatial relations between them, trees and graphs are composed of elements in an order or subset relationship (metaphorically, not directly spatial.) She gives a few examples of how we interpret maps (e.g., bar graphs suggest containers & make comparisons; line graphs suggest links & convey trends.) Tversky outlines two cognitive design principles: congruence (structure/content of viz should correspond to desired mental structure/content) and apprehension (structure/content should be readily & accurately perceived and comprehended.) She discusses two types of narrative in science viz: structure and process (the latter being more complex to depict.) For her, visual narratives should use analogy as well as present facts. While clarity and brevity are good in many situations, complexity sparks discovery and insight, so there are places for multiple types of diagrams.

Comments: Tversky’s general goal is to make use of schematic cognitive structures in the mind for design. She suggests several strategies for conveying concepts about process, including animations, arrows, and series of diagrams (as well as verbal descriptions.) She feels that animations are poorer in analogy, etc. than comic book format is (b/c animation mainly allows temporal links.) Perhaps interactivity would help address some of this concern about making different types of links.

Links to: Tufte 1, 2 (ideas about simplicity); Zhang & Norman (discussion of distributed cognition)

John K. Gilbert. “Visualization: An Emergent Field of Practice and Enquiry” in Science Education.” In John K. Gilbert, Miriam Reiner, and Mary Nakhleh (eds.) Visualization: Theory and Practice in Science Education, pp. 3-24. Dordrecht: Springer, 2008.

Summary: Gilbert discusses three levels of representation for scientific models: macroscopic, sub-microscopic (e.g., atoms, cells,) and symbolic (qualitative abstractions). External visualizations are used to create internal mental models; a key skill for full understanding is metavisualization, the ability to acquire, monitor, integrate, and extend from visualizations. He suggests two ways of classifying models: purpose (e.g., viz can be larger, smaller, show only processes, etc. of the subject) and dimensionality (e.g., 3-D ball & stick chem. models, 2-D diagrams, 1-D equations.) For metavisualization, people need to be able to understand the representation conventions for different dimensions, be able to translate between modes, construct their own representations, and solve problems using analogy by visualizations. He discusses challenges for mastery of conventions at different levels: macro representations are often taught in labs (they correspond with visible world); sub-micro level creates particular challenges for 3-D structures, but there’s a range of strategies for 2-D structures (e.g., diagrams, animations); and at the symbolic level one issue is differentiating between multiple systems (e.g., for chemical equations.) A key problem is being able to translate between levels (macro-micro-symbolic) or dimensions.

Comments: Traditional approach to mental models (internal vs. external), rather than distributed cognition. A lot of summary of classification systems and lists of skills needed to be visually literate. Goes into some detail about teaching strategies for developing metavisualization skills, which is not my main area of focus (except that multimedia may be good for this purpose.)

Links to: Zhang & Norman (distributed cognition view)

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exam readings information representation learning theory visuals

Exam readings: Distributed cognition and visualizations

For today, here are two related papers on distributed cognition (the idea that our thinking processes are intimately tied up with our environments, rather than being just internal) and images. The first paper presents a framework for understanding visualizations as part of distributed cognition, and the second applies that framework to studying interactive visualizations.

Jiajie Zhang, and Donald. A. Norman. “Representations in Distributed Cognitive Tasks.” Cognitive Science 18(1): 87-122, 1994.

Summary: In this paper, the authors present their theory of distributed cognition to describe how people conceptualize and perform tasks. Tasks are modeled using both internal and external components to create “distributed” representations. There are three basic problems in this view: the distributed representation of information, interaction between internal and external representations, and the nature of external representations. They discuss the “representational effect:” how different representations of the same information can have different cognitive effects (e.g., Roman vs. Arabic numerals and ease of calculation.) At issue here is that there are both internal and external “rules” in all problem representations; some formats contain more explicit or more easily understood external “rules,” which makes it easier to mentally interact with them. They outline a methodology for representational analysis that breaks done representations into component parts (skipping over details of this.) While external representations are aids to memory, they have additional functions: structuring (internal) cognition and providing information that does not need to be internalized in order to form a mental representation (affordances), and changing the fundamental nature of tasks.

Comments: The authors’ model of cognition suggests that differences among external representations will influence internal representations, or how information is learned. Practical implications include applicability of their ideas to effective design of representations. Not sure I will apply their methodology to my work, but theoretical approach is useful.

Links to: Kostelnick & Hassett (take rhetorical, rather than cognitive, approach to representation, point out that efficiency is usually not the driving force behind design); Liu et al. (argument to apply these ideas to info visualization)

Zhicheng Liu, Nancy J. Nersessian, and John T. Stasko. “Distributed Cognition as a Theoretical Framework for Information Visualization.” IEEE Transactions on Visualization and Computer Graphics. 14.6 (2008): 1173-1180.

Summary: The authors suggest using distributed cognition as a framework for information visualization research (not well-developed enough to serve as theory at this point-lacks predictive, prescriptive aspects.) Distributed cognition holds that cognition arises from the interaction of the mind with objects in the environment, rather than as just internal symbol processing as in the traditional view of cognition. The mind works by building an internal representation of an object that coordinates all the viewer’s external observations of the object; bringing the internal and external representations into agreement. Using this framework, we can look at interaction with data representations as the “propagation of representation states in a cognitive system through coordination;” i.e., as the process of building mental models. The act of manipulation helps us understand things (e.g., Tetris.) The authors also discuss the importance of testing how info visualization systems work in practice to help create mental models, rather than testing just ease of use or how well people like using a particular visualization.

Comments: Includes a discussion of Zhang’s and Norman’s “Representations” paper, which I’m also reading. The authors mention importance of linking research in interactive visualization to current cognitive science and perception research. This paper suggests both that interactivity is a useful property for building understanding and that holistic evaluation of mental models is appropriate for evaluating such interactions; they mention “social visualization:” sharing visualizations over the Web for exploring data representations.

Links to: Zhang & Norman