theoretical foundations evaluation
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1 amara Munzner, UBC CS, InfoVis Research problemdriven technique- work driven work theoretical foundations evaluation talk slides: 1
2 roblem-driven work design studies in collaboration with target users real data, real tasks intensive requirements analysis iterative refinement deploy tools/systems typical evaluation: field studies my strategy: opportunistic collaboration many domains both industrial and academic partners 2
3 roblem-driven: ech industry Heidi Lam Diane ang (Google) SessionViewer: web log analysis eter McLachlan Stephen North (A& Research) LiveRAC: systems time-series logs 3
4 roblem-driven: nergy, sustainability Matt Brehmer Kevin ate (ulse/nernoc) nergy Manager Maryam Booshehrian orsten Moeller (SU) Vismon 4
5 chr15 chr14 chr4 chrh chr1 chr4 roblem-driven: Genomics Aaron Barsky Jenn Gardy (UBC Micro) Robert Kincaid (Agilent) Miriah Meyer Hanspeter fister (Harvard) source: Human destination: Lizard chr17 chr18 chr19 chr20 chr21 chr22 chr6 chra chrx chrb chrc chrd chrf chry chrg chr1 Cerebral chr3 chr2 chr3 10Mb chr3 chr3 chr chr16 chr5 chr chr13 out in invert chr12 chr3 chr2 chr6 chr11 chr7 line saturation - + chr10 chr9 chr8 go to: orientation: match inversion MizBee MulteeSum, athline 5
6 roblem-driven: Genomics, journalism Joel erstay Cydney Nielsen (BC Cancer) Variant View Jonathan Stray (Assoc ress) Overview 6
7 roblem-driven: Autos, e-commerce Michael Sedlmair Relx (BMW) current work: Mobify clickstream collaboration Kimberly Dextras-Romagnino 7
8 echnique-driven work scalable algorithms & systems typical evaluation: computational benchmarks new layout & interaction techniques typical evaluation: controlled experiments on human subjects 8
9 echnique-driven: Graph drawing Daniel Archambault David Auber (Bordeaux) opolayout S Grouse Grouselocks uggraph Benjamin Renoust Detangler Guy Melançon (Bordeaux) reejuxtaposer 9
10 valuation experiments: Graph drawing Dmitry Nekrasovski Adam Bodnar Joanna McGrenere Stretch and squish navigation Jessica Dawson Joanna McGrenere Search set model of path tracing 10
11 echnique: Dimensionality reduction Stephen Ingram Glimmer DimStiller Glint QSN 11
12 Dimensionality reduction for documents derive low-dimensional target space from high-dimensional measured space ask 1 ask 2 ask 3 wombat In HD data Out 2D data In 2D data Out Scatterplot Clusters & points In Scatterplot Clusters & points Out Labels for clusters What? Why? What? Why? How? What? Why? In Highdimensional data Out 2D data roduce Derive In 2D data Out Scatterplot Out Clusters & points Discover xplore Identify ncode Navigate Select In Scatterplot In Clusters & points Out Labels for clusters roduce Annotate 12
13 valuation experiments: Dim. reduction Melanie ory oints vs landscapes for dimensionally reduced data Michael Sedlmair Melanie ory Guidance on DR & scatterplot choices axonomy of cluster separation factors 13
14 valuation in the field: Dim. reduction DR in the Wild Matt Brehmer Michael Sedlmair Melanie ory Stephen Ingram 14
15 Curation & resentation: imelines Johanna ulda (Sud. Zeitung) Matt Brehmer imelinecurator Bongshin Lee (Microsoft) Benjamin Bach (Microsoft) Nathalie Henry-Riche (Microsoft) imelines Revisited timelinesrevisited.github.io/ 15
16 heoretical foundations domain abstraction idiom apers rocess & itfalls algorithm Nested Model Design Study Methodology Michael Sedlmair Miriah Meyer Abstract asks Matt Brehmer 16
17 heoretical foundations Visualization Analysis & Design 17
18 Research agenda: interleaved angles of attack problemdriven technique- work driven work theoretical foundations evaluation talk slides: 18
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