Abstract
We describe an ontology matching method for efficient metadata integration in digital contents management system. This approach is using semantic integration methods in schema level but converts data from several data sources into a single queriable format in data level. Every data schema is represented by a ontology, and then the user generates mapping rules between metadata using the ontology mapping browser. Finally, all data are converted to a single data format and architecturally, this offers a tightly coupled approach because the data reside together in a single repository. In these processes, our study is providing user friendly and efficient methods to create relationships between metadata by semantic web technologies.
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
Data Integration in Wikipedia, http://en.wikipedia.org/wiki/Data_integration
Chaudury, S., Dayal, U.: An Overview of Data Warehousing and OLAP Technology. ACM SIGMOD Record 26(1), 65–74 (1997)
Lenzerini, M.: Data Integration: A Theoretical Perspective. In: Proceedings of The 21th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, pp. 233–246 (2002)
Hull, R., Zhou, G.: A framework for optimizing data integration using the materialized and virtual approaches. Technical report, Computer Science Department, University of Colorado (1996)
Halevy, A., Rajaraman, A., Ordille, J.: Data integration: the teenage years. In: Proceedings of The 32nd International Conference on Very Large Data Bases, Korea (2006)
Kolaitis, P.G.: Schema mappings, data exchange, and metadata management. In: Proceedings of The 24th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, Maryland (2005)
Ziegler, P., Dittrich, K.R.: Three Decades of Data Integration - All Problems Solved? In: Jacquart, R. (ed.) 18th IFIP World Computer Congress, vol. 12, pp. 3–12. Kluwer, Toulouse (2004)
Ziegler, P., Dittrich, K.R.: Data Integration — Problems, Approaches, and Perspectives. In: Conceptual Modelling in Information Systems Engineering, pp. 39–58. Springer, Heidelberg (2007)
Giunchiglia, F., Yatskevich, M., Shvaiko, P.: Semantic Matching: Algorithms and Implementation. In: Spaccapietra, S., Atzeni, P., Fages, F., Hacid, M.-S., Kifer, M., Mylopoulos, J., Pernici, B., Shvaiko, P., Trujillo, J., Zaihrayeu, I. (eds.) Journal on Data Semantics IX. LNCS, vol. 4601, pp. 1–38. Springer, Heidelberg (2007)
Al-Fares, M., Loukissas, A., Vahdat, A.: A scalable, commodity data center network architecture. In: ACM SIGCOMM Computer Communication Review, vol. 38(4) (2008)
Lee, S., Lee, M., Kim, P., Jung, H., Sung, W.: OntoFrame S3: Semantic Web-Based Academic Research Information Portal Service Empowered by STAR-WIN. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) The Semantic Web: Research and Applications. LNCS, vol. 6089, pp. 401–405. Springer, Heidelberg (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kim, P., Seo, D., Lee, M., Lee, S., Jung, H., Sung, WK. (2010). Ontology Matching Method for Efficient Metadata Integration. In: An, A., Lingras, P., Petty, S., Huang, R. (eds) Active Media Technology. AMT 2010. Lecture Notes in Computer Science, vol 6335. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15470-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-15470-6_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15469-0
Online ISBN: 978-3-642-15470-6
eBook Packages: Computer ScienceComputer Science (R0)