Readings 06: Scale
There are 4 required readings. The Munzner chapters are fairly short. The papers are somewhat light, especially since one of them is a survey (read it for the gist).
My comparisons paper (reading 3) generally gives you my thoughts on thinking about visualization in terms of comparison. It is the first place that the framework for thinking about scalability came up. In the paper, it is phrased in terms of comparison, but the ideas are more general (see reading 4). While sections 4 and 5 are the main pieces that deal with scale, I am having you read the whole paper now because I think it is useful in general (and this is the most logical place to put it). I believe that comparison is a generally useful way to think about visualization in general.
Our paper on Summary Visualization (reading 4) is a close up look at the scalability pieces introduced in the comparison paper. It tried to confirm that the three way categorization of scalability strategies from the earlier paper really covers everything we see in practice by doing a large survey. As a survey, it provides a lot of details and examples. It does introduce a fourth category, but mainly because it considers a broader range of things (it distinguishes reducing the number of items and number of dimensions, with comparison the latter is less relevant).
- (required) Reduce Items and Dimensions (Chapter 13 from Munzner’s Visualization Analysis & Design) (Munzner-13-Reduce.pdf 0.4mb)
- (required) Embed: Focus+Context (Chapter 14 from Munzner’s Visualization Analysis & Design) (Munzner-14-Embed.pdf 0.5mb)
- (required) Considerations for Visualizing Comparisons, Michael Gleicher, Info Vis 2017 (TVCG 2018). (web)
- (optional - but a skim through it is strongly recommended) Design Factors for Summary Visualization in Visual Analytics. Sarikaya, Gleicher and Szafir. (web) - This is a survey of different ways of doing summarization that appear in the visualization literature. There is a lot about how the survey was conducted, but the main thing for class is to see the different categories of summarization and how they interact.