Abstract
Most of the existing work on information integration in the Semantic Web concentrates on resolving schema-level problems. Specific issues of data-level integration (instance coreferencing, conflict resolution, handling uncertainty) are usually tackled by applying the same techniques as for ontology schema matching or by reusing the solutions produced in the database domain. However, data structured according to OWL ontologies has its specific features: e.g., the classes are organized into a hierarchy, the properties are inherited, data constraints differ from those defined by database schema. This paper describes how these features are exploited in our architecture KnoFuss, designed to support data-level integration of semantic annotations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kim, W., Seo, J.: Classifying schematic and data heterogeneity in multidatabase systems. IEEE Computer 24(12), 12–18 (1991)
Thor, A., Rahm, E.: MOMA - a mapping-based object matching system. In: 3rd Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA (2007)
Straccia, U., Troncy, R.: oMAP: Combining classifiers for aligning automatically OWL ontologies. In: Ngu, A.H.H., Kitsuregawa, M., Neuhold, E.J., Chung, J.-Y., Sheng, Q.Z. (eds.) WISE 2005. LNCS, vol. 3806. Springer, Heidelberg (2005)
Euzenat, J., Shvaiko, P.: Ontology matching. Springer, Heidelberg (2007)
Fellegi, I.P., Sunter, A.B.: A theory for record linkage. Journal of American Statistical Association 64(328), 1183–1210 (1969)
Elmagarmid, A.K., Ipeirotis, P.G., Verykios, V.S.: Duplicate record detection: A survey. IEEE Transactions on Knowledge and Data Engineering 19(1), 1–16 (2007)
Bilenko, M., Mooney, R.J.: Adaptive duplicate detection using learnable string similarity measures. In: 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2003), Washington, DC, pp. 39–48 (2003)
Rendle, S., Schmidt-Thieme, L.: Object identification with constraints. In: 6th IEEE International Conference on Data Mining (ICDM) (2006)
Jian, N., Hu, W., Cheng, G., Qu, Y.: Falcon-AO: Aligning ontologies with Falcon. In: K-CAP Workshop on Integrating Ontologies, Banff, CA, pp. 87–93 (2005)
Ehrig, M.: Ontology Alignment: Bridging the Semantic Gap. Springer, New York (2007)
Ehrig, M., Staab, S., Sure, Y.: Bootstrapping ontology alignment methods with APFEL. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 186–200. Springer, Heidelberg (2005)
Lee, Y., Sayyadian, M., Doan, A., Rosenthal, A.S.: eTuner: Tuning schema matching software using synthetic scenarios. VLDB Journal 16, 97–122 (2007)
Nikolov, A., Uren, V., Motta, E., de Roeck, A.: Using the Dempster-Shafer theory of evidence to resolve ABox inconsistencies. In: Workshop on Uncertainty Reasoning for the Semantic Web, ISWC 2007, Busan, Korea (2007)
Motta, E.: Reusable Components for Knowledge Modelling. Frontiers in Artificial Intelligence and Applications, vol. 53. IOS Press, Amsterdam (1999)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nikolov, A., Uren, V., Motta, E., de Roeck, A. (2008). Integration of Semantically Annotated Data by the KnoFuss Architecture. In: Gangemi, A., Euzenat, J. (eds) Knowledge Engineering: Practice and Patterns. EKAW 2008. Lecture Notes in Computer Science(), vol 5268. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87696-0_24
Download citation
DOI: https://doi.org/10.1007/978-3-540-87696-0_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87695-3
Online ISBN: 978-3-540-87696-0
eBook Packages: Computer ScienceComputer Science (R0)