1	Information Visualization Catherine Plaisant Human-Computer Interaction Laboratory University of Maryland
2	Information Visualization Catherine Plaisant Human-Computer Interaction Laboratory University of Maryland
3	Information Visualization Catherine Plaisant Human-Computer Interaction Laboratory University of Maryland
4	Seeing as understanding A common metaphor “I see what you mean” “To bring an issue in focus” “to make an idea clear”
5	Information Visualization: Using Vision to Think Visual bandwidth is enormous Human perceptual skills are remarkable Trend, cluster, gap, outlier... Color, size, shape, proximity... Human image storage is fast and vast Opportunities Spatial layouts & coordination Information visualization Scientific visualization & simulation Telepresence & augmented reality Virtual environments
6	Information Visualization: Definition Compact graphical presentation and user interface for manipulating large numbers of items (10² - 10⁶), possibly extracted from far larger datasets Enables users to make discoveries, decisions, or explanations about patterns (trend, cluster, gap, outlier...), groups of items, or individual items.
7	A classic example of early use of information visualization (see many more in Edward Tufte’s beautiful books)
8	Task by type taxonomy Information Visualization: Data Types 1-D Linear Document Lens, SeeSoft, Info Mural, Value Bars 2-D Map GIS, ArcView, Medical imagery 3-D World CAD, Medical, Molecules, Architecture Multi-Dim Parallel Coordinates, Spotfire, XGobi, Visage, Influence Explorer, TableLens, DEVise, many more Temporal Perspective Wall, LifeLines, Lifestreams, Project Managers, DataSpiral etc. Tree Cone/Cam/Hyperbolic, TreeBrowser, Treemap, etc. Network Netmap, netViz, SeeNet, Butterfly, Multi-trees
9	Task by type taxonomy Information Visualization: Tasks Overview Gain an overview of the entire collection Zoom Zoom in on items of interest Filter Filter out uninteresting items Details-on-demand Select an item or group and get details when needed Relate View relationships among items History Keep a history of actions to support undo, replay, and progressive refinement Extract Allow extraction of sub-collections and of the query parameters
10	"If a picture is worth..." If a picture is worth 1000 words…. An interface is worth 1000 pictures!
11
12	Dynamic Queries Direct manipulation strategies applied to querying Visual presentation of query components Visual presentation of results Rapid, incremental and reversible actions Selection by pointing (not typing) Immediate and continuous feedback Reduces errors Encourages exploration
13
14	Visual Information Seeking (The Design Principles which led to Spotfire) Dynamic queries Visual query formulation and immediate output Rapid, incremental and reversible actions Sliders, buttons, selectors Starfield display Complete overview: ordinal & categorical variables as axes Colored points of light reveal patterns Zoom bars to focus attention Tight coupling to preserve display invariants No errors Output becomes input Details-on-demand
15	Information Visualization Mantra Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand
16
17
18
19
20
21
22
23	Temporal data visualization LifeLines: Personal Graphical Histories Parallel lines color/size coded & grouped in categories Relationships among lines is viewable Related documents are viewable on-demand Zooming or hierarchical browsing allows focus+context Examples Youth histories & medical records Personal resumes, student records & performance reviews Challenges Aggregation & alerts Overview & detail views Easy import & export (Plaisant et al., CHI96) www.cs.umd.edu/hcil/LifeLines
24
25	Lifelines - Incident Data (from the Center for Advanced Transportation Technology, for the Maryland State Highway Administration)
26
27
28	Hierarchical data visualization: SpaceTree Large hierarchies Gain understanding of relationships among data Integrate search/browse
29	ConeTree
30	Treemap - view large trees with node values Space filling Space limited Color coding Size coding Requires learning
31	Treemap - Stock market, clustered by industry
32
33	Large volume of data e.g. Million-Item Treemap
34
35	Challenge of Graph Visualization
36
37	Fisheye views and Zooming User Interfaces Distortion to magnify areas of interest User-control, zoom factors of 3-5 Multi-scale spaces Zoom in/out & Pan left/right Smooth zooming Semantic zooming
38	DateLens
39	Zooming User Interfaces PhotoMesa – Zoomable Image Browser Browse large numbers of images See relationships among images Fast preview / detail Annotate & Search Cluster results
40	Spectrum of 3-D Visualizations Immersive Virtual Environment with head-mounted stereo display and head tracking Desktop 3-D for 3-D worlds medical, architectural, scientific visualizations Desktop 3-D for artificial worlds Bookhouse, file-cabinets, shopping malls Desktop 3-D for information visualization cone/cam trees, perspective wall, web-book SGI directories, Visible Decisions, Media Lab landscapes XGobi scatterplots, Themescape, Visage Chartjunk 3-D: barcharts, piecharts, histograms
41
42
43	WebBook-WebForager
44	Microsoft: Task Gallery
45
46	Challenge: Showing uncertainty and missing data
47
48
49	Color selection – Color blindness ColorBrewer www.colorbrewer.org VisCheck www.VisCheck.com
50	For More Information Chapter 14 on Info Visualization Shneiderman & Plaisant Designing the User Interface: Strategies for Effective Human-Computer Interaction: 4th Edition (2004) (www.aw.com/DTUI) Book of readings: Card, S., Mackinlay, J., and Shneiderman, B. Information Visualization: Using Vision to Think January 1999
51
52	Who we are About 10+ Faculty 10 Staff 30 Students
53	Who we are Interdisciplinary Group Computer Science Information Studies Psychology Biology Business English Education Engineering Government & Politics Part of UMIACS, the Institute for Advanced Computer Studies