Abstract
With the development of semantic web technologies, large and complex ontologies are constructed and applied to many practical applications. In order for users to quickly understand and acquire information from these huge information “oceans”, we propose a novel ontology visualization approach accompanied by “anatomies” of classes and properties. With the holistic “imaging”, users can both quickly locate the interesting “hot” classes or properties and understand the evolution of the ontology; with the anatomies, they can acquire more detailed information of classes or properties that is arduous to collect by browsing and navigation. Specifically, we produce the ontology’s holistic “imaging” which contains a semantic layout on classes and distributions of instances. Additionally, the evolution of the ontology is illustrated by the changes on the “imaging”. Furthermore, detailed anatomies of classes and properties, which are enhanced by techniques in database field (e.g. data mining), are ready for users.
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References
Tu, K., Xiong, M., Zhang, L., Zhu, H., Zhang, J., Yu, Y.: Towards imaging large-scale ontologies for quick understanding and analysis. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 702–715. Springer, Heidelberg (2005)
Kohonen, T.: Self-Organizing Maps. Springer, Heidelberg (1995)
Noy, N.F., Klein, M.: Ontology evolution: Not the same as schema evolution. SMI technical report SMI-2002-0926 (2002)
Klein, M., Noy, N.F.: A component-based framework for ontology evolution. In: Workshop on Ontologies and Distributed Systems at IJCAI 2003, Acapulco, Mexico (2003)
Pinto, H.S.A.N.P., Martins, J.P.: Evolving ontologies in distributed and dynamic settings. In: KR 2002, pp. 365–374 (2002)
Galiano, F.B., Marín, N.: Data mining: Concepts and techniques - book review. SIGMOD Record. 31, 66–68 (2002)
Fruchterman, T.M.J., Reingold, E.M.: Graph drawing by force-directed placement. Software - Practice and Experience 21, 1129–1164 (1991)
Du, Q., Faber, V., Gunzburger, M.: Centroidal voronoi tessellations: Applications and algorithms 41, 637–676 (1999)
Balzer, M., Deussen, O., Lewerentz, C.: Voronoi treemaps for the visualization of software metrics. In: SOFTVIS 2005, pp. 165–172 (2005)
Johnson, B., Shneiderman, B.: Tree maps: A space-filling approach to the visualization of hierarchical information structures. In: IEEE Visualization, pp. 284–291 (1991)
Zhang, L., Yu, Y., Lu, J., Lin, C., Tu, K., Guo, M., Zhang, Z., Xie, G., Su, Z., Pan, Y.: ORIENT: Integrate ontology engineering into industry tooling environment. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 823–837. Springer, Heidelberg (2004)
Sintek, E.: OntoViz: Ontoviz tab: Visualizing protege ontologies (2003)
Alani, H.: TGVizTab: An ontology visualization extension for protege. In: Knowledge Capture 2003 - Workshop on Visualizing Information in Knowledge Engineering, Sanibel Island, FL (2003)
Storey, M.A.D., Noy, N.F., Musen, M.A., Best, C., Fergerson, R.W., Ernst, N.: Jambalaya: an interactive environment for exploring ontologies. In: IUI 2002, p. 239 (2002)
Perrin, D.: Prompt-viz: Ontology version comparison visualizations with treemaps. Master’s thesis, University of Victoria, BC, Canada (2004)
Fluit, C., Sabou, M., van Harmelen, F.: Ontology-based information visualization. In: Proceedings of Information Visualization 2002 (2002)
Robinson, P.N., Böhme, U., Lopez, R., Mundlos, S., Nürnberg, P.: Gene-ontology analysis reveals association of tissue-specific 50 cpg-island genes with development and embryogenesis. Human Molecular Genetics 13, 1969–1978 (2004)
Cheng, J., Sun, S., Tracy, A., Hubbell, E., Morris, J., Valmeekam, V., Kimbrough, A., Cline, M.S., Liu, G., Shigeta, R., Kulp, D., Siani-Rose, M.A.: Netaffx gene ontology mining tool: a visual approach for microarray data analysis. Bioinformatics 20, 1462–1463 (2004)
Andrews, K., Kienreich, W., Sabol, V., Becker, J., Droschl, G., Kappe, F., Granitzer, M., Auer, P., Tochtermann, K.: The infosky visual explorer: exploiting hierarchical structure and document similarities. Information Visualization 1, 166–181 (2002)
Kaski, S., Honkela, T., Lagus, K., Kohonen, T.: Websom - self-organizing maps of document collections. Neurocomputing 21, 101–117 (1998)
Chen, H.C., Schuffels, C., Orwig, R.: Internet categorization and search: A selforganizing approach. Journal of Visual Communication and Image Representation 7, 88–102 (1996)
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Xiong, M., Chen, Y., Zheng, H., Yu, Y. (2006). Towards Quick Understanding and Analysis of Large-Scale Ontologies. In: Mizoguchi, R., Shi, Z., Giunchiglia, F. (eds) The Semantic Web – ASWC 2006. ASWC 2006. Lecture Notes in Computer Science, vol 4185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11836025_9
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DOI: https://doi.org/10.1007/11836025_9
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