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Informatics

Elastic Data for the Elastic Mind

Moritz Stefaner, a researcher at Fachhochschule Potsdam currently working on visualizations for the Eigenfactor project, applies cognitive science and design to the study of interfaces, visualization, statistics, and data mining. "Aesthetics in truly emergent informatics," he says, "is the perfect unity of information and form, and can only be achieved by an iterative interplay between creation and analysis. Great visualization is never a one-shot process." For his thesis work, Stefaner set out to produce visual tools for analyzing and revealing the interrelationship of data—or as he calls it, the "shape of information." An elastic tag map visualizes the connections between emerging keywords used to describe digital resources. An algorithm arranges tags by proximity on a 2D plane, while rollover action brings related keywords together—weighting relative probabilities of co-occurrence—and clicking locks the terms in place by semantic context. His elastic list of Nobel laureates generates customizable lists of prizewinners across multiple dimensions (discipline, gender, country, year), visualizing relative proportions by size, the characteristics of these proportions through brightness adjustments, and trends within each metadata point with embedded sparklines. Both of these tools have prototypical applications for next-generation search engines and digital interfaces. Watch the tools in action, while the designer explains:

For more information or to interact with the interfaces, visit well-formed-data.net.

Consideration

HOW DOES KNOWLEDGE EMERGE FROM DATA?

W. Bradford Paley is an interactive designer who teaches at Columbia University. He has been doing visual work on computers since 1973.

"Knowledge" and "data" are just names for different stages in sense making. I'd include "information" as another—though these are all just arbitrary terms until you put them into the context of a process (as the question does, with "emerge from"). If we consider a baby looking at an apple:

• 1Data. The receptors in a baby's retina send a signal downstream when a photon hits them. At very high light levels, that receptor may stop sending the signal; already, there is filtering. Then Retinal Ganglion cells immediately begin doing task-specific comparisons, increasing contrast among inputs in the retina, the beginning of…
• 2Information. Differences within the data. Several levels of extraction occur at ever more complex levels (contrast makes lines, lines make objects, objects exhibit properties and behaviors), each taking input from the last, finally feeding the high-level mental representations I think of as…
• 3Knowledge. Eventually, that baby will understand that it sees an apple, the child will learn it's good to eat, and the man might be able to build a mental model so general that its description of falling behavior evokes an "aha!" that can help describe the universe.

What's fascinating is that most of this process is not accessible to our conscious selves—the process itself is filtered out to allow consciousness to build the highest-level representations: knowledge, perhaps even wisdom? Knowing that every stage actively builds upon the last, that knowledge doesn't just passively "emerge," is profoundly important: It lets us realize we can enhance the process through proper presentation and training at the various levels. For instance, proper color use can make objects stand out or fade into the background; proper object shape can help us to visualize more easily what we're thinking about; proper organization can help us understand relationships more readily; proper training in logic (or even domain-specific rules of thumb) can help us build more robust and flexible mental models. A good part of human culture, especially the practice of science, is exactly this: honing and extending our ability to think.

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The Fundamentals: Informatics
Posted November 20, 2008
Originally appeared in Seed 19