Part 5: Data Visualization and Interactive Interface Design

This is Part 5 of 7 of the highlights from “Illuminating the Path: The Research and Development Agenda for Visual Analytics.” Please see this post for an introduction to the study and access to the other 6 parts.

Data Visualization

The visualization of information “amplifies human cognitive capabilities in six basic ways” by:

  • Increasing cognitive resources, such as by using a visual resource to expand human working memory;
  • Reducing search, such as by representing a large amount of data in a small place;
  • Enhancing the recognition of patterns, such as when information is organized in space by its time relationships;
  • Supporting the easy perceptual inference of relationships that are otherwise more difficult to induce;
  • Enabling perceptual monitoring of a large number of potential events;
  • Providing a manipulable medium that, unlike static diagrams, enables the exploration of a space of parameter values.

The table below provides additional information on how visualization amplifies cognition:

NAVCsTable

Clearly, “these capabilities of information visualization, combined with computational data analysis, can be applied to analytic reasoning to support the sense-making process.” The National Visualization and Analysis Center (NVAC) thus recommends developing “visually based methods to support the entire analytic reasoning process, including the analysis of data as well as structured reasoning techniques such as the construction of arguments, convergent-divergent investigation, and evaluation of alternatives.”

Since “well-crafted visual representations can play a critical role in making information clear [...], the visual representations and interactions we develop must readily support users of varying backgrounds and expertise.” To be sure, “visual representations and interactions must be developed with the full range of users in mind, from the experienced user to the novice working under intense pressure [...].”

As NVACs notes, “visual representations are the equivalent of power tools for analytical reasoning.” But just like real power tools, they can cause harm if used carelessly. Indeed, it is important to note that “poorly designed visualizations may lead to an incorrect decision and great harm. A famous example is the poor visualization of the O-ring data produced before the disastrous launch of the Challenger space shuttle [...].”

Effective Depictions

This is why we need some basic principles for developing effective depictions, such as the following:

  • Appropriateness Principle: the visual representation should provide neither more or less information than that needed for the task at hand. Additional information may be distracting and makes the task more difficult.
  • Naturalness Principle: experiential cognition is most effective when the properties of the visual representation most closely match the information being represented. This principle supports the idea that new visual metaphors are only useful for representing information when they match the user’s cognitive model of the information. Purely artificial visual metaphors can actually hinder understanding.
  • Matching Principle: representations of information are mst effective when they match the task to be performed by the user. Effective visual representations should present affordances suggestive of the appropriate action.
  • Congruence Principle: the structure and content of a visualization should correspond to the structure and content of the desired mental representation.
  • Apprehension Principle: the structure and content of a visualization should be readily and accurately perceived and comprehended.

Further research is needed to understand “how best to combine time and space in visual representation. “For example, in the flow map, spatial information is primary” in that it defines the coordinate system, but “why is this the case, and are there visual representations where time is foregrounded that could also be used to support analytical tasks?”

In sum, we must deepen our understanding of temporal reasoning and “create task-appropriate methods for integrating spatial and temporal dimensions of data into visual representations.”

Interactive Interface Design

It is important in the visual analytics process that researchers focus on visual representations of data and interaction design in equal measure. “We need to develop a ‘science of interaction’ rooted in a deep understanding of the different forms of interaction and their respective benefits.”

For example, one promising approach for simplifying interactions is to use 3D graphical user interfaces. Another is to move beyond single modality (or human sense) interaction techniques.

Indeed, recent research suggests that “multi-modal interfaces can overcome problems that any one modality may have. For example, voice and deictic (e.g., pointing) gestures can complement each other and make it easier for the user to accomplish certain tasks.” In fact, studies suggest that “users prefer combined voice and gestural communication over either modality alone when attempting graphics manipulation.”

Patrick Philippe Meier

8 responses to “Part 5: Data Visualization and Interactive Interface Design

  1. Pingback: Research Agenda for Visual Analytics « iRevolution

  2. Okay yes! Twitterverse and microblogging has gotten the global conversation streams rocking – viz around that is the language of the stream – the synthesizing mind that Howard Gardner talks about is the global reader (i.e., connective, collective cognition) and the pattern language is datavis. Data Vis is the Esperanto of the new millenium!

  3. Patrick thanks again for a great writeup — I honestly would not have expected anyone related to homeland security to be quoting Tufte and Norman. … But when they cite the need to create a “Science of interaction,” I wonder how much exposure NVAC has in the existing interaction design community. Perhaps they just mean that the existing community is not rigorous enough (I would love to talk more about that; it certainly could be a valid criticism).

    Somehow I can’t see these guys chatting it up on the Interaction Design Association list.

    I think the things that they are talking about doing are so ambitious that it would a few departments in universities (if not “a new science”).

    Since they are talking about seriously complex and sensitive data, not improving checkout ratios for e-commerce, which is what most interaction designers do, unfortunately.

    So, I’m intrigued, I support their efforts, and I hope that they are not thinking that they are the only ones equipped to do this new work!

    • Hi Chris, many thanks for reading and for your thoughts and feedback on NVAC’s work. I’ve invited Kris Cook, the co-author of the NVAC study to participate in our Crisis Mapping conference, so very much hoping you’ll have the opportunity to interact directly with her.

      Cheers!

  4. unthinkinglychris

    Can’t wait to have my mind blown at the conference. Putting the word out here in Cambodia.

  5. Pingback: Proposing the Field of Crisis Mapping « iRevolution

  6. Pingback: Week 10: Individual Action and the Bigger Picture « Beginia Cheung

  7. Good stuff! I`ll be following.

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