1. Information Visualisation Praminda Caleb-Solly

2. Learning Objectives Gain an understanding of the benefits of information visualisation Explore ways of visualising different types of information

3. What is Visualisation? Definitions of Visualisation: –graphical presentation of information, often dependent on categorisation or clustering techniques to bring out patterns in the information. members.optusnet.com.au/~webindexing/Webbook2Ed/glos sary.htm members.optusnet.com.au/~webindexing/Webbook2Ed/glos sary.htm –Display of data in a manner meaningful to the user. This doesn't necessarily imply sophisticated multi-dimensional graphics. In many cases tradition 2D line graphs are the most meaningful method of interpretation. www.dfusion.com.au/information/glossary.htm www.dfusion.com.au/information/glossary.htm Definitions of scientific visualisation: –Scientific visualization is a branch of computer graphics which is concerned with the presentation of interactive or animated digital images to scientists who interpret potentially huge quantities of laboratory or simulation data or the results from sensors out in the field. en.wikipedia.org/wiki/Scientific_visualisation en.wikipedia.org/wiki/Scientific_visualisation

4. Information Visualization Applicability Bergeron has defined the following classification –exploratory visualization (undirected search) –analytical visualization (directed search) –descriptive visualization Decision making

5. What are the benefits of Information Visualisation? Parallel Perceptual Processing Offload Work from Cognitive to Perceptual System Expanded Working Memory Expanded Storage of Information Locality of Processing High Data Intensity Spatially Indexed Addressing Recognition Instead of Recall Abstraction and Aggregation Visual Representations Make Some Problems Obvious Perceptual Monitoring Manipulability of Medium

6. Some Visualisation Demos Treemapshttp://www.hivegroup.com/demos /amazon/3017951.htmlhttp://www.hivegroup.com/demos /amazon/3017951.html LifeLines Scientific Visualisation\1998_lifelines.mpgScientific Visualisation\1998_lifelines.mpg Visual Thesaurus http://www.visualthesaurus.com/ http://www.visualthesaurus.com/

7. Process for visualisation Source: http://www.cs.vu.nl/~frankh/postscript/VSW01.pdf//

8. A process for visualization? Card, Stuart K., Mackinlay, Jock D. & Shniederman, Ben. (1999). Readings in Information Visualization: Using Vision to Think. Academic Press.

9. Visualization and Ontologies What is an ontology: http://www.dictionary.com http://www.dictionary.com –An explicit formal specification of how to represent the objects, concepts and other entities that are assumed to exist in some area of interest and the relationships that hold among them –The hierarchical structuring of knowledge about things by subcategorizing them according to their essential (or at least relevant and/or cognitive) qualities

10. T. Berners-Lee et al, in Scientific American, May 2001

11. SVG Demos SVG is an acronym for Scalable Vector Graphics and is a W3C standard. It's a language for describing two- dimensional graphics and graphical applications in XML. http://www.adobe.com/svg/demos/

12. Further Demos http://www.cems.uwe.ac.uk/~phale/Rectang leDemo/RectangleDemo.viewlet/Rectangle Demo_launcher.htmlhttp://www.cems.uwe.ac.uk/~phale/Rectang leDemo/RectangleDemo.viewlet/Rectangle Demo_launcher.html Further example http://www.cems.uwe.ac.uk/~phale/Interacti veSVGExamples.htm http://www.cems.uwe.ac.uk/~phale/Interacti veSVGExamples.htm

13. References Bergeron, D. (1993) Visualization reference models (panel session position statement). In G.M. Nielson and D. Bergeron, editors, Proceedings of Visualization '93, IEEE Computer Science Press. Card S., Mackinlay J, and Shneiderman B. (1999) Readings in Information Visualization: Using Vision to Think, Morgan Kaufmann. Spence R. (2001) Information Visualization, ACM Press/Addison Wesley Tufte, E. 2001, The Visual Display of Quantitative Information, Graphics Press Ware C. (2000) Information Visualization: Perception for Design, Morgan Kaufmann

14. Enabling Technologies XSLT style sheets that generate SVG output based on XML input –XSLT engine to transform the source data and an SVG viewer RDF for ontology definition

15. Issues in Scientific Data Management Creating Collections Physical Data Handling Interoperability between collections Data Ownership and Security Persistence Metadata definition Knowledge Discovery Data dissemination and presentation

16. Some Application Areas Chemistry Genomics Astronomy Geography Bioinformatics

17. 1932 London Underground Map

18. Harry Beck’s 1933 London Tube Map

19. A recent tube map

20. What are the benefits of Information Visualisation? Card, Stuart K., Mackinlay, Jock D. & Shniederman, Ben. (1999). Readings in Information Visualization: Using Vision to Think. Academic Press.