Share Email Print

Proceedings Paper

Visualizing abstract information using motion properties of data-driven infoticles
Author(s): Andrew Vande Moere; Kuk Hwan Mieusset; Markus Gross
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

This paper presents a novel exploratory information visualization technique that allows users to analyze time-varying characteristics of large datasets within immersive virtual reality environments. This metaphor represents data objects as particles, coined infoticles, which are placed inside a three-dimensional scene. Forces correspond to specific data value conditions and influence matching infoticles according to the rules of Newtonian mechanics. In addition, infoticles are driven by a set of local behavior rules that react upon successive data updates, hereby generating distinct emergent motion typologies which are visually interpretable by users. These data patterns can be detected dynamically by observing the spatial transformations of infoticle streams, or statically, by interpreting the shapes of individual pathlines. This visualization method exploits the qualities of immersive virtual reality technology as it combines the characteristics of behavior generation and motion perception with the concepts of spatial awareness and stereoscopic vision. Infoticles are useful in visualizing time-varying characteristics of large, dynamic datasets because of their cognitively distinguishable and interpretative animation properties. The generation and evolution of infoticle patterns are based upon empirically defined grammatical rules. These visualization principles are demonstrated using the access logs of an internal knowledge document management website of a global consultancy company.

Paper Details

Date Published: 4 June 2004
PDF: 12 pages
Proc. SPIE 5295, Visualization and Data Analysis 2004, (4 June 2004); doi: 10.1117/12.539238
Show Author Affiliations
Andrew Vande Moere, Swiss Federal Institute of Technology Zurich (Switzerland)
Kuk Hwan Mieusset, Swiss Federal Institute of Technology Zurich (Switzerland)
Markus Gross, Swiss Federal Institute of Technology Zurich (Switzerland)

Published in SPIE Proceedings Vol. 5295:
Visualization and Data Analysis 2004
Robert F. Erbacher; Philip C. Chen; Jonathan C. Roberts; Matti T. Gröhn; Katy Börner, Editor(s)

© SPIE. Terms of Use
Back to Top