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Bilal Alsallakh Wolfgang Aigner Silvia Miksch Helwig Hauser Radial Sets: Interactive Visual Analysis of Large Overlapping Sets
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Euler Diagrams Limited scalability Potentially overlaps Drawability not guaranteed Difficult to identify certain overlaps Overlaps are salient features Analysis tasks often related to finding and comparing them 2
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Radial Sets 3 set-membership degree [adapted from Wyatt‘s Set Visualizer]
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The Overlaps Absolute size Relative size Deviation from marginal independence 3 rd -degree overlaps 4
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5 Overview First! Details on Demand
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Interactive Selection New selection (B) click Combine new and existing selection (A) click + 6
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Video Showing interactions with the user interface http://www.youtube.com/watch?v=UcYRrPqC5A8 7
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Reducing Overlaps Clutter 8
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Scalability 9 35 sets26 sets 6 Sets7 Sets11 Sets
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Limitations 10 Containment relations unsupported Visual complexity Histogram bars Centered => no baseline Radial Arrangement
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Applications Survey data Multi-label classifications Comparing different classifiers 11
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Conclusion New metaphor Aggregation-based Highly-interactive Handles about 30 sets Visual complexity Future work: Analytics Handling large sets 12 www.radialsets.org
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Backup Slides Evaluation Aggregations Other Approachs Ordering the Set Regions Set-typed Data Tasks related to Set typed Data Set Regions - 3D Cues Comparison with Parallel Sets 13
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Evaluation Ongoing user study 20 subjects by now Answer questions related to the tasks T1.. T7 (refer to the paper) Some features excluded (e.g. high-dgree overlaps, as they need more time than available to explain). Frist results highly positive! After 10 min. explanation, the metaphor was easy to understand 14
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Aggregations 15 Set elements into bars Overlaps into links Attribute values into color Multiple bars into one bar
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Other Approachs 16
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Element-set Matrix / Overlap Matrix vs. Radial Sets 17
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Set‘o‘grams vs. Radial Sets 18
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Venn vs. Euler Diagarm A Venn diagram depicts all possible overlaps (incl. empty ones) An Euler diagram depict actual (non-empty) overlaps only 19
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Ordering the Set Regions 20
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Set-typed Data Appear in different forms Multiple rows Boolean attributes Multi-valued attributes Number of sets Number of elements Other data attributes 21
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Tasks related to Set typed Data How do elements belong to the sets? Which ones are exclusive to a set, or belong to k sets. How do set overlaps Which sets exhibit more overlaps Which elements belong to certain overlaps How is an attribute distributed? in the sets or in selected subsets therefore in the overlaps 22
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Set Regions: 3D Cues 23
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Comparison with Contingency Wheel++ Contingency tables vs. set memberships Different aggregation Different semantics New visual representations Interactions for set operations Overlap analysis view But share the basic idea 24
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Comparison with Parallel Sets Parallel Sets Designed for Categorical Data Can be subdivided further Handles a small number of categories 25 Eye/HairBlackBrownRedBlond Brown68119297 Blue20841794 Hazel15541410 Green52914
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