1	The Happy Marriage of Geographic Information Systems and Information Visualization Ben Shneiderman ben@cs.umd.edu Founding Director (1983-2000), Human-Computer Interaction Lab Professor, Department of Computer Science Member, Institutes for Advanced Computer Studies & Systems Research University of Maryland College Park, MD 20742
2
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 Libary
11	Zooming User Interfaces
12	ZUI: Pocket PhotoMesa
13	PhotoMesa
14
15
16	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)
17	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
18	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.
19	Information Visualization: US Research Centers Xerox PARC 3-D cone trees, perspective wall, spiral calendar table lens, hyperbolic trees, document lens Univ. of Maryland dynamic queries, range sliders, starfields, treemaps, timeboxes, zoombars tight coupling, dynamic pruning, lifelines IBM, Microsoft, AT&T Georgia Tech, MIT Media Lab, CMU Univ. of Wisconsin, Minnesota, Calif-Berkeley Pacific Northwest National Labs
20
21	Highway Incidents on Baltimore Beltway (Fredikson, Plaisant, North & Shneiderman, 1999)
22
23	Information Visualization: Design Guidelines Direct manipulation strategies 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
24
25
26
27
28
29	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
30	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-Dim 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
31
32
33
34
35
36
37
38
39	Treemap: view large trees with node values Space filling Space limited Color coding Size coding Requires learning
40	Treemap: Stock market, clustered by industry
41
42
43
44	PairTrees: Treemap and Choropleth Map
45	Hierarchical Clustering Explorer
46	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
47	Challenges: GIS & InfoViz Dealing with large volume of data Also problem of missing data, uncertainty Combining visual with textual representations Collaborative exploration Environments for publishing results, sharing knowledge Large shared displays Integrating with data mining Specialized toolkits and development tools Addressing Universal Usability Evaluation: Empirical studies, observations, case studies
48
49	Challenges: Make a Better World Science & Medicine E-Commerce & Finance Digital Government Agriculture & Environment Transportation & Housing
50	Leonardo da Vinci (1452-1519) Inspirational Muse For the New Computing
51
52	Upcoming Events
53	For More Information Visit the HCIL website for 350 papers & info on videos www.cs.umd.edu/hcil Conferences & resources: www.infovis.org See Chapter 14 on Info Visualization Shneiderman, B. and Plaisant, C., Designing the User Interface: Strategies for Effective Human-Computer Interaction: Fourth Edition (April 2004) www.awl.com/DTUI Edited Collections: Card, S., Mackinlay, J., and Shneiderman, B. (1999) Readings in Information Visualization: Using Vision to Think Bederson, B. and Shneiderman, B. (2003) The Craft of Information Visualization: Readings and Reflections
54	For More Information Treemaps HiveGroup: www.hivegroup.com Smartmoney: www.smartmoney.com/marketmap HCIL Treemap 4.1: www.cs.umd.edu/hcil/treemap Spotfire: www.spotfire.com TimeSearcher: www.cs.umd.edu/hcil/timesearcher Hierarchical Clustering Explorer: www.cs.umd.edu/hcil/hce