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SemLens: visual analysis of semantic data with scatter plots and semantic lenses

Published:07 September 2011Publication History

ABSTRACT

Querying the Semantic Web and analyzing the query results are often complex tasks that can be greatly facilitated by visual interfaces. A major challenge in the design of these interfaces is to provide intuitive and efficient interaction support without limiting too much the analytical degrees of freedom. This paper introduces SemLens, a visual tool that combines scatter plots and semantic lenses to overcome this challenge and to allow for a simple yet powerful analysis of RDF data. The scatter plots provide a global overview on an object collection and support the visual discovery of correlations and patterns in the data. The semantic lenses add dimensions for local analysis of subsets of the objects. A demo accessing DBpedia data is used for illustration.

References

  1. Bier, E., Stone, M., Pier, K., Buxton, W. and DeRose, T. 1993. Toolglass and Magic Lenses: The See-Through Interface. In: Proc. of SIGGRAPH '93. ACM, 73--80. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R. and Hellmann, S. 2009. DBpedia -- A Crystallization Point for the Web of Data. Journal of Web Semantics, 7, 3, 154--165. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Borsje, J., and Embregts, H. 2006. Graphical Query Composition and Natural Language Processing in an RDF Visualization Interface. Bachelor thesis. Erasmus University Rotterdam.Google ScholarGoogle Scholar
  4. Hearst, M. 2006. Design Recommendations for Hierarchical Faceted Search Interfaces. In: ACM SIGIR Workshop on Faceted Search, Seattle, Washington.Google ScholarGoogle Scholar
  5. Hildebrand, M., Ossenbruggen, J. and Hardman, L. 2006./facet: A Browser for Heterogeneous Semantic Web Repositories. In: Proc. of ISWC '06. Springer, 272--285. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Huynh, D. and Karger, D. 2009. Parallax and Companion: Set-based Browsing for the Data Web, http://davidhuynh.net/media/papers/2009/www2009-parallax.pdfGoogle ScholarGoogle Scholar
  7. iSPARQL, http://dbpedia.org/isparql/Google ScholarGoogle Scholar
  8. Russell, A., Smart, P. R., Braines, D. and Shadbolt, N. R. 2008. NITELIGHT: A Graphical Tool for Semantic Query Construction. In: Proc. of SWUI '08, Florence, Italy.Google ScholarGoogle Scholar
  9. Schraefel, M. C., Smith, D., Owens, A., Russell, A., Harris, C. and Wilson, M. 2005. The Evolving mSpace Platform: Leveraging the Semantic Web on the Trail of the Memex. In: Proc. of HYPERTEXT '05. ACM, 174--183. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. SemLens, http://semlens.visualdataweb.orgGoogle ScholarGoogle Scholar
  11. Stone, M. C., Fishkin, K. and Bier, E. A. 1994. The Movable Filter as a User Interface Tool. In: Proc. of CHI '94. ACM, 306--312. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. W3C SWEO Linking Open Data Community Project, http://www.w3.org/wiki/SweoIG/TaskForces/Google ScholarGoogle Scholar
  13. Ware, C., Purchase, H., Colpoys, L. and McGill, M. 2002. Cognitive measurements of graph aesthetics. Information Visualization, 1, 2, 103--110. Google ScholarGoogle ScholarDigital LibraryDigital Library

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        cover image ACM Other conferences
        I-Semantics '11: Proceedings of the 7th International Conference on Semantic Systems
        September 2011
        129 pages
        ISBN:9781450306218
        DOI:10.1145/2063518

        Copyright © 2011 ACM

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        New York, NY, United States

        Publication History

        • Published: 7 September 2011

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