information visualisation

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Information Visualisation Praminda Caleb-Solly

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Information Visualisation. Praminda Caleb-Solly. Learning Objectives. Gain an understanding of the benefits of information visualisation Explore ways of visualising different types of information. What is Visualisation?. Definitions of Visualisation : - PowerPoint PPT Presentation

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Information Visualisation

Praminda Caleb-Solly

Learning Objectives

• Gain an understanding of the benefits of information visualisation

• Explore ways of visualising different types of information

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/glossary.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

• 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

Information Visualization Applicability

• Bergeron has defined the following classification

– exploratory visualization (undirected search)

– analytical visualization (directed search)

– descriptive visualization

• Decision making

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

Some Visualisation Demos• Treemaps

http://www.hivegroup.com/demos/amazon/3017951.html

• LifeLines Scientific Visualisation\1998_lifelines.mpg

• Visual Thesaurus http://www.visualthesaurus.com/

Process for visualisation

Source: http://www.cs.vu.nl/~frankh/postscript/VSW01.pdf/

A process for visualization?

RawData

DataTables

VisualStructures Views

User / Task

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

Visualization and Ontologies

• What is an ontology: 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

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

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/

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

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

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

Some Application Areas

• Chemistry• Genomics• Astronomy• Geography• Bioinformatics

1932 London Underground Map

Harry Beck’s 1933 London Tube Map

A recent tube map

What are the benefits of Information Visualisation?Parallel perceptual processing Some attributes of visualizations can be processed in parallel

compared to text.

Offload work from cognitive to perceptual system

Some cognitive inferences done symbolically can be recoded into inferences done with simple perceptual operations.

Expanded working memory Visualizations can expand the working memory available for solving a problem.

Expanded storage of information

Visualizations can be used to store massive amounts of information in a quickly accessible form (e.g., maps).

Locality of processing Visualizations group information used together, reducing searching.

High data intensity Visualizations can often present a large amount of data in a small space.

Spatially indexed addressing By grouping data about an object, visualizations can avoid symbolic labels.

Recognition instead of recall Recognizing information generated by a visualization is easier than recalling that information by that user.

Abstraction and aggregation Visualizations simplify and organize information, supplying higher centers with aggregated forms of information through abstraction and selective omission.

Visual representations make some problem obvious

Visualizations can support a large number of perceptual inferences that are extremely easy for humans.

Perceptual monitoring Visualizations can allow for the monitoring of a large number of potential events if the display is organized so that these stand out by appearance or motion.

Manipulable medium Unlike static diagrams, visualizations can allow exploration of a space of parameter values and can amplify user operations.

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