1	Information Visualization for Knowledge Discovery Ben Shneiderman ben@cs.umd.edu Founding Director (1983-2000), Human-Computer Interaction Lab Professor, Department of Computer Science Member, Institute for Advanced Computer Studies University of Maryland College Park, MD 20742
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3	Scientific Approach (beyond user friendly) Specify users and tasks Predict and measure time to learn speed of performance rate of human errors human retention over time Assess subjective satisfaction (Questionnaire for User Interface Satisfaction) Accommodate individual differences Consider social, organizational & cultural context
4	Design Issues Input devices & strategies Keyboards, pointing devices, voice Direct manipulation Menus, forms, commands Output devices & formats Screens, windows, color, sound Text, tables, graphics Instructions, messages, help Collaboration & communities Manuals, tutorials, training
5	U.S. Library of Congress Scholars, Journalists, Citizens Teachers, Students
6	Visible Human Explorer (NLM) Doctors Surgeons Researchers Students
7	NASA Environmental Data Scientists Farmers Land planners Students
8	Bureau of the Census Economists, Policy makers, Journalists Teachers, Students
9	NSF Digital Government Initiative Find what you need Understand what you Find
10	International Children’s Digital Library
11	Piccolo: Toolkit for 2D zoomable objects Structured canvas of graphical objects in a hierarchical scenegraph Zooming animation Cameras, layers Open, Extensible & Efficient Java, C#, PocketPC versions www.cs.umd.edu/hcil/piccolo
12	Information Visualization The eye… the window of the soul, is the principal means by which the central sense can most completely and abundantly appreciate the infinite works of nature. Leonardo da Vinci (1452 - 1519)
13	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
14	Spotfire: Retinol’s role in embryos & vision
15	Spotfire: DC natality data
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17	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
18	Information Visualization: Data Types 1-D Linear Document Lens, SeeSoft, Info Mural, Value Bars 2-D Map GIS, ArcView, PageMaker, Medical imagery 3-D World CAD, Medical, Molecules, Architecture Multi-Var Parallel Coordinates, Spotfire, XGobi, Visage, Influence Explorer, TableLens, DEVise Temporal Perspective Wall, LifeLines, Lifestreams, Project Managers, DataSpiral Tree Cone/Cam/Hyperbolic, TreeBrowser, Treemap Network Netmap, netViz, SeeNet, Butterfly, Multi-trees
19	ManyEyes: A web sharing platform
20	Treemap: view large trees with node values Space filling Space limited Color coding Size coding Requires learning
21	Treemap: Stock market, clustered by industry
22	Market falls steeply Feb 27, 2007, with one exception
23	Market falls 311 points July 26, 2007, with a few exceptions
24	Market mixed, October 22, 2007, Energy & Basic Material are down
25	Market mixed, February 8, 2008 Energy & Technology up, Financial & Health Care down
26	Market rises 319 points, November 13, 2007, with 5 exceptions
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28	Treemap: Gene Ontology
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33	LifeLines: Customer Histories Temporal data visualization Medical patient histories Customer relationship management Legal case histories
34	Temporal Data: TimeSearcher 1.3 Time series Stocks Weather Genes User-specified patterns Rapid search
35	Temporal Data: TimeSearcher 2.0 Long Time series (>10,000 time points) Multiple variables Controlled precision in match (Linear, offset, noise, amplitude)
36	Goal: Find Features in Multi-Var Data Clear vision of what the data is Clear goal of what you are looking for Systematic strategy for examining all views Ranking of views to guide discovery Tools to record progress & annotate findings
37	Multi-V: Hierarchical Clustering Explorer
38	Do you see anything interesting?
39	What features stand out?
40	Correlation…What else?
41	… and Outliers
42	Demonstration US counties census data 3138 counties 14 dimensions : population density, poverty level, unemployment, etc.
43	Rank-by-Feature Framework: 1D
44	Rank-by-Feature Framework: 2D
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46	HCE Status In collaboration and sponsored by Eric Hoffman: Children’s National Medical Center Phd work of Jinwook Seo 72K lines of C++ codes 4,000+ downloads since April 2002 www.cs.umd.edu/hcil/hce
47	Evaluation Methods Ethnographic Observational Situated Multi-Dimensional In-depth Long-term Case studies
48	Evaluation Methods Ethnographic Observational Situated Multi-Dimensional In-depth Long-term Case studies Domain Experts Doing Their Own Work for Weeks & Months
49	Evaluation Methods Ethnographic Observational Situated Multi-Dimensional In-depth Long-term Case studies
50	MILC example Evaluate Hierarchical Clustering Explorer Focused on rank-by-feature framework 3 case studies, 4-8 weeks (molecular biologist, statistician, meteorologist) 57 email surveys Identified problems early, gave strong positive feedback about benefits of rank-by-feature
51	MILC example Evaluate SocialAction Focused on integrating statistics & visualization 4 case studies, 4-8 weeks (journalist, bibliometrician, terrorist analyst, organizational analyst) Identified desired features, gave strong positive feedback about benefits of integration
52	Case Study Methodology 1) Interview (1 hr) 2) Training (2 hr) 3) Early Use (2-4 weeks) 4) Mature Use (2-4 weeks) 5) Outcome (1 hr)
53	Take Away Message Rank-by-Feature Framework Decomposition of complex problems into multiple simpler problems wins Ranking guides discovery Systematic strategies www.cs.umd.edu/hcil/hce
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