Visualization of Heterogeneous Data

Published Articles >> Table of Contents >> Abstract

November/December 2007 (Vol. 13, No. 6) pp. 1200-1207
Visualization of Heterogeneous Data
Mike Cammarano
Xin (Luna) Dong
Bryan Chan, IEEE
Jeff Klingner, IEEE Computer Society
Justin Talbot
Alon Halevey, IEEE Computer Society
Pat Hanrahan, IEEE Computer Society

Full Article Text:

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2007.70617
Send link to a friend

Abstract
Both the Resource Description Framework (RDF), used in the semantic web, and Maya Viz u-forms represent data as a graph of objects connected by labeled edges. Existing systems for flexible visualization of this kind of data require manual specification of the possible visualization roles for each data attribute. When the schema is large and unfamiliar, this requirement inhibits exploratory visualization by requiring a costly up-front data integration step. To eliminate this step, we propose an automatic technique for mapping data attributes to visualization attributes. We formulate this as a schema matching problem, finding appropriate paths in the data model for each required visualization attribute in a visualization template.
About References \| Back to Top References
[1] ${\rm d\bar oj\bar o}$ javascript toolkit. http:/dojotoolkit.org/. [2] Information commons. http://www.maya.cominfocommons/. [3] Maya Viz. http://www.mayaviz.com/web/concepts/downloads viz_comotion_overview.pdf. [4] Programmableweb. http:/www.programmableweb.com/. [5] Resource description framework (rdf). http://www.w3.orgRDF/. [6] Simile timeline. http://simile.mit.edutimeline/. [7] S. Auer, C. Bizer, R. Cyganiak, O. Erling, K. Idehen, G. Kobilarov, J. Lehmann, J. Schöuppel http:/dbpedia.org/. [8] A. Balmin, V. Hristidis, N. Koudas, Y. Papakonstantinou, D. Srivastava, and T. Wang, A system for keyword search on xml databases. In VLDB (demo), pages 1069–1072, 2003. [9] J. Bertin, The Semiology of Graphics. Univ. of Wisconsin Press, 1984. [10] A. Buja, D. Cook, and D. F. Swayne, Interactive high-dimensional data visualization. Computational and Graphical Statistics, 5 (1): 78–99, 1996. [11] S. P. Callahan, J. Freire, E. Santos, C. E. Scheidegger, C. T. Silva, and H. T. Vo, VisTrails: Visualization meets data management. In Sigmod, pages 745–747, 2006. [12] T. Catarci, M. F. Costabile, S. Levialdi, and C. Batini, Visual query systems for databases: a survey. Journal of Visual Languages and Computing, 8 (2): 215–260, 1997. [13] J. Chen, L. Sun, O. R. Zaiane, and R. Goebel, Visualizing and discovering web navigational patterns. In WebDB, pages 13–18, 2004. [14] D. R. Cutting, D. R. Karger, J. O. Pedersen, and J. W. Tukey, Scatter/Gather: A cluster-based approach to browsing large document collections. In SIGIR, pages 318–329, 1992. [15] M. Dubinko, R. Kumar, J. Magnani, J. Novak, P. Raghavan, and A. Tomkins, Visualizing tags over time. In WWW, pages 193–202, 2006. [16] M. Franklin, A. Halevy, and D. Maier, From databases to dataspaces: A new abstraction for information management. Sigmod Record, 34 (4): 27–33, 2005. [17] G. W. Furnas and S. J. Rauch, Considerations for information environments and the NaviQue workspace. INEX Workshop, pages 79–88, 2003. [18] R. Goldman and J. Widom, Interactive query and search in semistructured databases. In WebDB, pages 52–62, 1998. [19] GoogleBase. http:/base.google.com/, 2005. [20] P. Hanrahan, VizQL: A language for query, analysis and visualization. In Sigmod, page 721, 2006. [21] J. Heer, S. K. Card, and J. A. Landay, prefuse: a toolkit for interactive information visualization. In CHI '05: Proceedings of the SIGCHI conference on Human factors in computing systems, pages 421–430, 2005. [22] V. Hristidis, Y. Papakonstantinou, and A. Balmin, Keyword proximity search on xml graphs. In International Conference on Data Engineering, pages 367–378, 2003. [23] D. R. Karger, K. Bakshi, D. Huynh, D. Quan, and V. Sinha, Haystack: A general-purpose information management tool for end users of semistructured data. In CIDR, pages 13–26, 2005. [24] D. A. Keim, Information visualization and visual data mining. IEEE Transactions on Visualization and Computer Graphics, 7 (1): 1–8, 2002. [25] D. A. Keim and H.-P. Kriegel, VisDB: Database exploration using multidimensional visualization. IEEE Computer Graphics and Applications, 14 (5): 40–49, 1994. [26] Y. Li, C. Yu, and H. V. Jagadish, Schema-free xquery. In VLDB, pages 72–83, 2004. [27] M. Livny, R. Ramakrishnan, K. S. Beyer, G. Chen, D. Donjerkovic, S. Lawande, J. Myllymaki, and R. K. Wenger, DEVise: Integrated querying and visualization of large datasets. In Sigmod, pages 301–312, 1997. [28] J. Mackinlay, Automating the design of graphical presentations of relational information. ACM Trans. Graph., 5 (2): 110–141, 1986. [29] J. Madhavan, P. A. Bernstein, A. Doan, and A. Halevy, Corpus-based schema matching. In ICDE, pages 57–68, 2005. [30] C. Olston, M. Stonebraker, A. Aiken, and J. M. Hellerstein, VIQING: Visual interactive querying. In VL, pages 162–169, 1998. [31] M. Petropoulos, A. Deutsch, and Y. Papakonstantinou, Interactive query formulation over web service-accessed sources. In Sigmod, pages 253–264, 2006. [32] S. Polyviou, G. Samaras, and P. Evripidou, A relationally complete visual query language for heterogeneous data sources and pervasive querying. In ICDE, pages 471–482, 2005. [33] E. Rahm and P. A. Bernstein, A survey of approaches to automatic schema matching. VLDB Journal, 10 (4): 334–350, 2001. [34] S. F. Roth, J. Kolojejchick, J. Mattis, and J. Goldstein, Interactive graphic design using automatic presentation knowledge. In CHI '94: Proceedings of the SIGCHI conference on Human factors in computing systems, pages 112–117, New York, NY, USA, 1994. ACM Press. [35] S. F. Roth, P. Lucas, J. A. Senn, C. C. Gomberg, M. B. Burks, P. J. Stroffolino, J. A. Kolojejchick, and C. Dunmire, Visage: A user interface environment for exploring information. In Information Visualization, pages 3–16, 1996. [36] G. Salton, editor. The SMART Retrieval System—Experiments in Automatic Document Retrieval. Prentice Hall, Englewood Cliffs, NJ, 1971. [37] V. Sinha and D. R. Karger, Magnet: Supporting navigation in semistructured data environments. In Sigmod, pages 97–106, 2005. [38] C. Stolte, D. Tang, and P. Hanrahan, Polaris: A system for query, analysis and visualization of multidimensional relational databases. IEEE Transaction on Visualization and Computer Graphics, 8 (1): 52–65, 2002. [39] M. Stonebraker, Visionary: A next generation visualization system for data bases. In Sigmod, page 635, 2003. [40] A. Trigoni, Interactive query formulation in semistructured databases. In FQAS, pages 356–369, 2002. [41] S. Wang, Z. Peng, J. Zhang, L. Qin, S. Wang, J. X. Yu, and B. Ding, NUITS: A novel user interface for efficient keyword search over databases. In VLDB, pages 1143–1146, 2006. [42] M. O. Ward, XmdvTool: Integrating multiple methods for visualzing multivariate data. In Visualization, pages 326–333, 1994. [43] L. Wilkinson and G. Wills, The Grammar of Graphics. Springer, 2005. [44] J. Wong and J. I. Hong, Making mashups with marmite: Towards enduser programming for the web. In CHI '07: Proceedings of the SIGCHI conference on Human Factors in computing systems, pages 1435–1444. ACM Press, 2007. [45] K.-P. Yee, K. Swearingen, K. Li, and M. Hearst, Faceted metadata for image search and browsing. In CHI, pages 401–408, 2003.
Back to Top Additional Information
Index Terms- Data integration, RDF, attribute inference Citation: Mike Cammarano, Xin (Luna) Dong, Bryan Chan, Jeff Klingner, Justin Talbot, Alon Halevey, Pat Hanrahan, "Visualization of Heterogeneous Data," IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, pp. 1200-1207, Nov/Dec, 2007

RSS Feed

	Advanced Search
CS Search Google Search