1. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady1 MAT 259 Visualizing Information Winter 2006, e-studio, Art 2220 Tues 10:00-12:00, Lecture Thurs 10:00-12:00, Lab George Legrady, legrady@arts.ucsb.edulegrady@arts.ucsb.edu TA Angus Forbes, angus.forbes@gmail.comangus.forbes@gmail.com Course Web Site : http://www.mat.ucsb.edu/~g.legrady/ (click on “courses”, click on “MAT 259”)http://www.mat.ucsb.edu/~g.legrady/

2. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady2 Course Goals  An introduction to information visualization  An overview of varied methodologies  Comparison between uses in diverse disciplines  Introduction to self-organizing algorithms  Project driven course with focus on theory and practice 1)Working with cultural data, 2)Exploration of methodologies, 3)Visualization output to reflect aesthetic consideration

3. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady3 Workload  Attendance at weekly lectures  Active participation  Online reports on readings  Attendance & reports on visiting lectures  Completion of warm-up and final projects

4. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady4 Visualization & Cross-Disciplinary Fertilization  Domain visualization, an emerging field  Multi-disciplinary: Difficult to get the overview of the field  Researchers bring their own discipline’s perspective  Examination of other disciplines: export and import of methods, ideas, models, or empirical results  Creative imagination required to foresee how outside info fits the problem at hand

5. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady5 Discipline Driven Methodologies  Each discipline has a particular implementation goal  LSIS: citation indexing, bibliographic indexing, etc.  Scientific Visualization: Map physical phenomena in 2D, or 3D  Information Visualization: Analyzing and transforming nonspatial data into visual form  Geographic Information Systems (GIS): Cartographic framework, a familiar way to map data  Art: Aesthetics, complexity, culturally meaningful results

6. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady6 Goal Driven Methodologies  Information Visualization: visually map abstract, nonspatial info  Information retrieval research in vast data sets  Depicting the overall semantic structure of a set of documents  Identifying patterns through visualization (DNA)

7. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady7 User Meta Model  Data Extraction  Definition of Units of Analysis  Selection of Measures  Calculation of similarity between units  Ordination: assignments of coordinates to each unit  Analysis and Interpretation of output visualization

8. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady8 Classification Methods  Alphabetical: arbitrary learned system  Numeric: arbitrary learned system  Scalar: (hotel star system) implies value scale  Sequential (time): based on units  Spatial: “sense of place”  Categories: similar things grouped together  Associative: (If a to b, then c to d)  Metaphoric: A way to establish context  Random: Creates complexity (game beginnings)

9. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady9 Visualization Process  Multivariate data to be presented in 2D in print or computer screen  by applying mathematical dimensionality algorithms to map the data  Clustering techniques to group similar data  Spatial proximity matrix: similar data/close, difference/distance  Large amounts of data presented in limited space:  Panning, zooming, filtering to access data

10. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady10 What is Visualization?  Design of the visual appearance of data objects and their relationships  Ability to comprehend large amounts of data  Reduction in search time through visualization  Provides a better understanding of complex data sets  Reveal relationships and properties through visual perception  Multiple simultaneous perspectives  Effective communication

11. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady11 Formal & Aesthetic Functions  Visualization Design: years of expertise and diverse skills  Visual communication: a language system (function of form, colors, etc)  Complex data relationship benefit from storytelling  Narrative methods enhance communication

12. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady12 Interaction Design  Search and browse through data  Zoom, filtering, panning, etc.  1) Overview, 2) Zoom-in (filter), 3) Details-on-demand  “Browsing explores both the organization or structure of the information space, and its content” (Chen, 1998)  Information architects design layered info spaces based on classification systems  3 Navigational Paradigms: 1) spatial, 2) semantic, 3) social (using behavior of like-minded people) (Dourish)

13. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady13 Visualization Outcomes  Effective exploitation of perceptual principles  Helps communication with non-specialists  Discover hidden (semantic) patterns, structures  Contribute to knowledge development in all disciplines

14. Media Arts and Technology Graduate Program UC Santa Barbara MAT 259 Visualizing Information Winter 2006George Legrady14 References (Selected)  “Visualizing Knowledge Domains”, Borner, Chen, Boyak  Journal of Information Visualization  Kohonen Self-Organizing Algorithm  Visual Complexity  Information Aesthetics  Edward Tufte