Abstract
Recently, several approaches and systems were proposed to store in the same database data and the ontologies describing their meanings. We call these databases, ontology-based databases (OBDBs). Ontology-based data denotes those data that represent ontology individuals (i.e., instance of ontology classes). To speed up query execution on the top of these OBDBs, efficient representations of ontology-based data become a new challenge. Two main representation schemes have been proposed for ontology-based data: vertical and binary representations with a variant called hybrid. In these schemes, each instance is split into a number of tuples. In this paper, we propose a new representation of ontology-based data, called table per class. It consists in associating a table to each ontology class, where all property values of a class instance are represented in a same row. Columns of this table represent those properties of the ontology class that are associated with a value for at least one instance of this class. We present the architecture of our ontology-based databases and a comparison of the effectiveness of our representation scheme with the existing ones used in Semantic Web applications. Our benchmark involves three categories of queries: (1) targeted class queries, where users know the classes they are querying, (2) no targeted class queries, where users do not know the class(es) they are querying, and (3) update queries.
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References
Agrawal, R., Somani, A., Xu, Y.: Storage and querying of e-commerce data. In: Proc. VLDB’01, pp. 149–158 (2001)
Alexaki, S., Christophides, V., Karvounarakis, G., Plexousakis, D., Tolle, K.: On storing voluminous rdf descriptions: The case of web portal catalogs. In: Proc. ofWebDB’01 (co-located with ACM SIGMOD’01), ACM Press, New York (2001), citeseer.ist.psu.edu/alexaki01icsforth.html
McBride, B.: Jena: Implementing the rdf model and syntax specification. In: Proc. of the 2nd Intern. Workshop on the Semantic Web (2001)
Broekstra, J., Kampman, A., van Harmelen, F.: Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 54–68. Springer, Heidelberg (2002)
Chawathe, S.S., Garcia-Molina, H., Hammer, J., Ireland, K., Papakonstantinou, Y., Ullman, J.D., Widom, J.: The tsimmis project: Integration of heterogeneous information sources. In: Proceedings of the 10th Meeting of the Information Processing Society of Japan, pp. 7–18. Marsh (1994)
Dean, M., Schreiber, G.: Wl web ontology language reference. W3C Recommendation (February 2004)
Dehainsala, H., Pierra, G., Bellatreche, L.: Managing instance data in ontology-based databases. Technical report, LISI-ENSMA (2006), http://www.lisi.ensma.fr/ftp/pub/documents/reports/2006/2006-LISI-003-DEHAINSALA.pdf
Harris, S., Gibbins, N.: 3store: Efficient bulk rdf storage. In: Proc. of the 1st Intern. Workshop on Practical and Scalable Semantic Systems, PSSS’03 (2003)
IEC. Iec 61360 - component data dictionary. International Electrotechnical Commission (2001), Available at http://dom2.iec.ch/iec61360?OpenFrameset
Ma, L., Su, Z., Pan, Y., Zhang, L., Liu, T.: Rstar: an rdf storage and query system for enterprise resource management. In: Thirteenth ACM international conference on Information and knowledge management, pp. 484–491 (2004)
Pan, Z., Heflin, J.: Dldb: Extending relational databases to support semantic web queries. In: ISWC (2003)
Pierra, G.: A multiple perspective object oriented model for engineering design. New Advances in Computer Aided Design & Comp. Graphics, 368–373 (1993)
Pierra, G.: Context-explication in conceptual ontologies: Plib ontologies and their use for industrial data. To appear in Journal of Advanced Manufacturing Systems (2006), available at http://www.lisi.ensma.fr/ftp/pub/documents/papers/2006/2006-JAMS-Pierra.pdf
Stoffel, K., Taylor, M.G., Hendler, J.A.: Efficient management of very large ontologies. In: Proc. of American Association for Artificial Intelligence Conference, AAAI’97 (1997)
Theoharis, Y., Christophides, V., Karvounarakis, G.: Benchmarking Database Representations of RDF/S Stores. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 685–701. Springer, Heidelberg (2005)
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Dehainsala, H., Pierra, G., Bellatreche, L. (2007). OntoDB: An Ontology-Based Database for Data Intensive Applications. In: Kotagiri, R., Krishna, P.R., Mohania, M., Nantajeewarawat, E. (eds) Advances in Databases: Concepts, Systems and Applications. DASFAA 2007. Lecture Notes in Computer Science, vol 4443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71703-4_43
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DOI: https://doi.org/10.1007/978-3-540-71703-4_43
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