Mick McQuaid

Consider Yi’s list with respect to a particular project, the Tacoma Crime Data project.

It’s typical to view crimes and density of crimes. What about victims and their traffic patterns? Where do they go and how long do they stay there? I’ve lived in several cities where the crime downtown at night is high, but nonexistent during the workday. Two completely different populations seem to inhabit the same space. I’ve also lived in one city where a main artery to downtown was a crime-ridden street with cheap motels leading from a freeway exit. As a result, many people drove through a high-crime area in commuting, but never stopped. Can you follow a group of victims for 24 hours before they became victims? Can you follow them and follow others? (select)

Are crimes related? A recent Economist article about legalized prostitution in two countries contrasted the results, saying that one country still experienced high levels of other crime associated with prostitution while the other country did not. One key difference was that the method of legalization in one case required the prostitutes to affiliate with an institution while the other did not. The country with the institutional requirement found that organized crime fulfilled it. This suggests that a visualization of types of crime may be more informative if it is coupled with a visualization of types of criminals. (explore)

Do you have any way of sorting on different variables? Does the value of sorting suggest a non-cartographic representation? (reconfigure)

How many values does each variable have? Do some variables map better to color encoding and others map better to shape? Should you use multiple modalities to encode the same information? For example, should severity be shown by a combination of color and size? (encode)

I use Google maps at different levels of detail in planning a single trip. Suppose I were to do that with crime data overlaid. How would that change when I zoom in and out? (abstract / elaborate)

We’ve discussed hierarchies and whether some are somehow more natural or more privileged than other categories. Suppose you can let the user filter the data to be visualized. Can you establish some kind of ranking of the most important or most likely criteria for filtering? Would it change your design? Suppose, for instance, you could filter on attributes of the victim or of the criminal. Which would be the default? (filter)

Crime data seems so complicated that cries out for techniques like brushing, where you select (brush) an item in one view to highlight it in another view. For example, time and location are most easily in different representations, but I may want to know when crimes occur in a given location or where crimes occur at a certain time. (connect)

Interaction in Information Visualization

Yi et al. (2007) begins by dividing InfoVis into two components, representation and interaction. Do you believe that distinction? Why do you suppose I assert four components: information and users in addition to Yi’s components? Where does context fit into either of these models? Note that there is a community of researchers on the theme of User Modeling and that they often try to personalize applications by understanding user context. That community includes some of the scholars such as Alfred Kobsa whose papers you have read in this course. You may want to consider how congruent their main objective is with the notion of using InfoVis to reduce information overload.

We’ve previously discussed varying definitions of InfoVis and the tendency of some authors to relax the interaction requirement to define static images as InfoVis. What do you think of Yi’s description of interactions with static images, including rotating, looking closer / further, and annotating? What about the idea that a passive interaction changes or enhances the mental model of a data set. For example, I showed you a static image of i-Schools generated by a multidimensional scaling of terms in course descriptions, reproduced below.

I told you that we can see two communities and a crescent of schools whose identities are more disparate. You can perhaps imagine that a particular viewer’s mental model of this data set will change based on level of familiarity with one or the other community, or with the issues facing the disparate schools.

How do you define interaction? There is probably a typo in Yi et al. where they mention “direction manipulation” and presumably mean direct manipulation. You all have experience with direct manipulation. Do you restrict your frame of reference to this interaction style? What other interaction styles have you learned and possibly used?

Yi et al. draw on prior work to suggest three ways to evaluate models: their ability to describe a relevant set of alternatives (needs generality), their ability to inform evaluations of alternatives (needs concreteness), and their ability to help create new designs (needs openness). It might be useful to look at the following model with this criteria in mind. Why do you think they claim that existing models don’t satisfy these three criteria simultaneously? What role do you think affinity diagramming might have played in the leap from (A) listing techniques to (B) settling on user intent as a grouping mechanism?

Yi’s main contribution is a detailed discussion of the following list of interaction categories.