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Multi-Dimensional Data Visualization 2

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  1. Multi-Dimensional Data Visualization 2 cs5984: Information Visualization Chris North

  2. Homework #1 • Due today

  3. Star Coordinates • Continue discussion… • Kandogan, “Star Coordinates” • Rohit, David

  4. Table Lens • Rao, “Table Lens” • Harsha, Vishal

  5. VisDB • Keim, “VisDB” • Ming, Rui

  6. Comparison of tools • Parcood: <1000 items, <20 attrs • Relate between adjacent attr pairs • Starcoord: <1,000,000 items, <20 attrs • Interaction intensive • Tablelens: similar to par-coords • more items with aggregation • Relate 1:m attrs (sorting), short learn time • Visdb: 100,000 items with 10 attrs • Items*attrs = screenspace, loooong learn time, must query! • Spotfire: <1,000,000 items, <10+infinity attrs • Filtering, short learn time

  7. Next Week • Book chapter 5 • Tues: Dynamic Queries • Tweedie, Spence, “Externalizing Abstract Mathematical Models” (Attribute/Influence Explorer) • wang, alli • Doan, “Query Previews” • anuj, vikrant • Thurs: Multi-D Functions • Feiner, “Worlds within Worlds” • sandip, ben • vanWijk “HyperSlice” • kumar, kunal

  8. Project • Proposal due next Thurs, Sept 13 • Team, project description • Projects: • Human-eye view -alex • Online chat/video-conference visualization (virtual school) • Mahesh • samel • Bioinformatics – experiment vis in context -Quoc • Gene patterns? • Digital libraries, Envision 2 groups • Snap-together visualization - nathan -ying • Visualizing Multi-D functions - sanjini -mishra • Visualization in the periphery - david • Visualization of data structures - kunal