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Comparison in Infovis Summary Report of Comparison in Information Visualization Group

Comparison in Infovis Summary Report of Comparison in Information Visualization Group. Dagstuhl Seminar 10241 Information Visualization

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Comparison in Infovis Summary Report of Comparison in Information Visualization Group

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  1. Comparison in Infovis Summary Report of Comparison in Information Visualization Group Dagstuhl Seminar 10241Information Visualization Beck, Fabian;Diehl, Stephan;Dwyer, Tim; Gleicher, Michael;Hansen, Charles;Jusufi, llir;Ma, Kwan-Liu;Perer, Adam;Roberts, Jonathan C. ;Yang, Jing;Zeckzer, Dirk;

  2. Design Space • juxaposition, separation, small multiples • memory to make connection: • overlay, superimpose • visuals to make connection: • fusion, difference objects, derived representation, finding context • analysis to make connection: • example: bar charts • juxtapose: side-by-side • fusion: stack chart

  3. Mathematical representation

  4. Infovis issues • showing context: do you show changes in isolation or in context, how much context do you show? • heterogenous data: graph comparison, text comparison, time series comparison, but rich data type comparison has not really been explored... • complexity of mapping between entities we want to compare (1:0, 1:1, 1:Many, Many:Many) • Ordering (if n-way comparison): • traveling sales-man problem to find a sequence of things such that most similar pairs are adjacent • domain specific

  5. Issues (across & down) • Comparing across different forms? • if comparing items that can be represented in multiple ways (e.g. graphs, equations, etc) need to find a normal / common form / or find largest similar subgraph (isomorphism). • May not even be a 1-1 matching possible • Partiality of comparison (esp. across different hierarchies/ aggregations) • Something in one view & not in another (may be off screen, contained, or not within projection) • Missing values • Uncertainty

  6. Issues (temporality) • animation is juxtaposition in time • How to depict change? • draw "trajectories" to link similar items that have moved spatially • continuous difference vs. discrete difference : • example video analysis, compare discrete samples versus overlaying all frames (blur around changes) • Hierarchy to support navigation • Allows for semantic zoom (focus+context) • Where does it come from? • Given in data or • Computed (e.g. clustering) • relationships • perceptual issues • degree of change

  7. Issues Navigation & comparison in infovis • need to drill down compare & drill up to compare • Abstraction/simplification/generalization vs. details • graph navigation, abstraction • Examples of similar problems in CMV systems

  8. Cross-cutting model • who does comparison? • human reasoning • visual encoding/analytic process • know the difference: • Know what to compare, show it explicitly • don't know but need to find it let the user decide + Right task for the right view + Interaction solves your tough problems by letting the user set the course of action

  9. Comparison for infovis • All visualizations can be augmented with comparison in mind • Comparison views are challenging but useful • No inherent spatial embedding • Free to design embedding to highlight diffs • We have a responsibility to design appropriate encodings • Comparison is another data point (value) • Degree of interest metric in comparison is degree of change • Are there similarities to visualizing uncertainty

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