Facet Juxtapose and coordinate views Lectures 3&4: Juxtapose Share Encoding: Same/Di fg erent Facet & Reduce Linked Highlighting Partition Facet Into Multiple Views Share Data: All/Subset/None Tamara Munzner Department of Computer Science University of British Columbia Superimpose Share Navigation DSCI 532, Data Visualization 2 Week 2, Jan 9 / Jan 11 2018 www.cs.ubc.ca/~tmm/courses/mds-viz2-17 @tamaramunzner 2 3 4 Idiom: Small multiples System: Cerebral Eyes beat memory Coordinate views: Design choice interaction Why not animation? • encoding: same • disparate frames and • principle: external cognition vs. internal memory regions: comparison • data: none shared –easy to compare by moving eyes between side-by-side views All Subset None difficult –harder to compare visible item to memory of what you saw –different attributes Overview/ –vs contiguous frames for node colors • implications for animation Same Redundant Detail –vs small region –(same network –great for choreographed storytelling Small Multiples layout) –vs coherent motion of group –great for transitions between two states Multiform, • navigation: shared No Linkage –poor for many states with changes everywhere Overview/ Multiform Detail • safe special case • consider small multiples instead • why juxtapose views? –animated transitions literal abstract –benefits: eyes vs memory animation small multiples • lower cognitive load to move eyes between 2 views than remembering previous state with show time with time show time with space single changing view [Cerebral: Visualizing Multiple Experimental Conditions on a Graph with Biological Context. Barsky, Munzner, Gardy, and Kincaid. IEEE Trans. –costs: display area, 2 views side by side each have only half the area of one view Visualization and Computer Graphics (Proc. InfoVis 2008) 14:6 (2008), 1253–1260.] 5 6 7 8 Change blindness Idiom: Linked highlighting System: EDV Linked views Linked views: Multidirectional linking System: Buckets • if attention is directed elsewhere, even drastic changes not noticeable • see how regions contiguous in one • unidirectional vs bidirectional linking view are distributed within another –door experiment –powerful and pervasive • change blindness demos interaction idiom –mask in between images • encoding: different –multiform • data: all shared • aka: brushing and linking [Visual Exploration of Large Structured Datasets. Wills. Proc. New Techniques http://buckets.peterbeshai.com/ and Trends in Statistics (NTTS), pp. 237–246. IOS Press, 1995.] https://medium.com/@pbesh/linked-highlighting-with-react-d3-js-and-reflux-16e9c0b2210b http://www.ralphstraumann.ch/projects/swiss-population-cartogram/ http://peterbeshai.com/linked-highlighting-react-d3-reflux/ 9 10 11 12 System: Google Maps Idiom: Overview-detail views Idiom: Overview-detail navigation System: Improvise Partition into views • encoding: same • encoding: same • investigate power • how to divide data between views Partition into Side-by-Side Views of multiple views • data: subset shared • data: subset shared –split into regions by attributes –pushing limits on –encodes association between items • navigation: shared • navigation: shared view count, using spatial proximity interaction –bidirectional linking –unidirectional linking –order of splits has major implications complexity –select in small overview for what patterns are visible –how many is ok? • differences –change extent in large detail view • no strict dividing line • open research question https://www.highcharts.com/ –viewpoint –view: big/detailed demo/dynamic-master-detail –reorderable lists –(size) • contiguous region in which visually • easy lookup encoded data is shown on the display • useful when linked to other –glyph: small/iconic • special case: [A Review of Overview+Detail, Zooming, and Focus+Context Interfaces. encodings Cockburn, Karlson, and Bederson. ACM Computing Surveys 41:1 (2008), • object with internal structure that arises birds-eye map 1–31.] from multiple marks [Building Highly-Coordinated Visualizations In Improvise. Weaver. Proc. IEEE Symp. Information Visualization (InfoVis), pp. 159–166, 2004.] https://bl.ocks.org/mbostock/34f08d5e11952a80609169b7917d4172 13 14 15 16
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