Exploring semantic social networks using virtual reality

Conference Paper

We present Redgraph, the first generic virtual reality visualization program for Semantic Web data. Redgraph is capable of handling large data-sets, as we demonstrate on social network data from the U.S. Patent Trade Office. We develop a Semantic Web vocabulary of virtual reality terms compatible with GraphXML to map graph visualization into the Semantic Web itself. Our approach to visualizing Semantic Web data takes advantage of user-interaction in an immersive environment to bypass a number of difficult issues in 3-dimensional graph visualization layout by relying on users themselves to interactively extrude the nodes and links of a 2-dimensional graph into the third dimension. When users touch nodes in the virtual reality environment, they retrieve data formatted according to the data's schema or ontology. We applied Redgraph to social network data constructed from patents, inventors, and institutions from the United States Patent and Trademark Office in order to explore networks of innovation in computing. Using this data-set, results of a user study comparing extrusion (3-D) vs. no-extrusion (2-D) are presented. The study showed the use of a 3-D interface by subjects led to significant improvement on answering of fine-grained questions about the data-set, but no significant difference was found for broad questions about the overall structure of the data. Furthermore, inference can be used to improve the visualization, as demonstrated with a data-set of biotechnology patents and researchers. © 2008 Springer Berlin Heidelberg.

Full Text

Duke Authors

Cited Authors

  • Halpin, H; Zielinski, DJ; Brady, R; Kelly, G

Published Date

  • January 1, 2008

Published In

Volume / Issue

  • 5318 LNCS /

Start / End Page

  • 599 - 614

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

International Standard Serial Number (ISSN)

  • 0302-9743

International Standard Book Number 10 (ISBN-10)

  • 3540885633

International Standard Book Number 13 (ISBN-13)

  • 9783540885634

Digital Object Identifier (DOI)

  • 10.1007/978-3-540-88564-1_38

Citation Source

  • Scopus