ANALYSIS OF ONTOLOGICAL INSTANCES - A Data Warehouse for the Semantic Web

Roxana Danger, Rafael Berlanga

Abstract

New data warehouse tools for Semantic Web are becoming more and more necessary. The present paper formalizes one such a tool considering, on the one hand, the semantics and theorical foundations of Description Logic and, on the other hand, the current developments of information data generalization. The presented model is constituted by dimensions and multidimensional schemata and spaces. An algorithm to retrieve interesting spaces according to the data distribution is also proposed. Some ideas from Data Mining techniques are incorporated in order to allow users to discover knowledge from the Semantic Web.

References

  1. Abelló, A. (2002). YAM2: A Multidimensional Conceptual Model. PhD thesis, Universitat Politécnica de Catalunya.
  2. Baader, F. and Sattler, U. (2003). Description logics with aggregates and concrete domains. Inf. Syst., 28(8):979-1004.
  3. Binh, N. T. and Tjoa, A. M. (2001). Conceptual multidimensional data model based on object-oriented metacube. In SAC 7801: Proceedings of the 2001 ACM symposium on Applied computing, pages 295- 300. ACM Press.
  4. Buzydlowski, J. W., Song, I.-Y., and Hassell, L. (1998). A framework for object-oriented on-line analytic processing. In DOLAP 7898: Proceedings of the 1st ACM international workshop on Data warehousing and OLAP, pages 10-15. ACM Press.
  5. Carter, C. L. and Hamilton, H. J. (1998). Efficient attributeoriented generalization for knowledge discovery from large databases. IEEE Transactions on Knowledge and Data Engineering, 10(2):193-208.
  6. Danger, R. (2007). Extracción y análisis de información desde la perspectiva de la Web Semántica (Information extraction and analysis from the viewpoint of Semantic Web, in spanish). PhD thesis, Universitat Jaime I.
  7. Hacid, M.-S. and Sattler, U. (1998). Modeling multidimensional databases: A formal object-centered approach. In Proceedings of the Sixth European Conference on Information Systems.
  8. Han, J. and Kamber, M. (2001). Data Mining: Concepts and Techniques. Morgan Kaufmann.
  9. Han, J., Nishio, S., Kawano, H., and Wang, W. (1998). Generalization-based data mining in object-oriented databases using an object cube model. Data Knowledge Engineering, 25(1-2):55-97.
  10. Nguyen, T. B., Tjoa, A. M., and Wagner, R. (2000). An object oriented multidimensional data model for OLAP. In Web-Age Information Management, pages 69-82.
  11. Trujillo, J., Palomar, M., Gómez, J., and Song, I.-Y. (2001). Designing data warehouses with OO conceptual models. Computer, 34(12):66-75.
Download


Paper Citation


in Harvard Style

Danger R. and Berlanga R. (2007). ANALYSIS OF ONTOLOGICAL INSTANCES - A Data Warehouse for the Semantic Web . In Proceedings of the Second International Conference on Software and Data Technologies - Volume 3: ICSOFT, ISBN 978-989-8111-07-4, pages 13-20. DOI: 10.5220/0001332200130020


in Bibtex Style

@conference{icsoft07,
author={Roxana Danger and Rafael Berlanga},
title={ANALYSIS OF ONTOLOGICAL INSTANCES - A Data Warehouse for the Semantic Web},
booktitle={Proceedings of the Second International Conference on Software and Data Technologies - Volume 3: ICSOFT,},
year={2007},
pages={13-20},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001332200130020},
isbn={978-989-8111-07-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Software and Data Technologies - Volume 3: ICSOFT,
TI - ANALYSIS OF ONTOLOGICAL INSTANCES - A Data Warehouse for the Semantic Web
SN - 978-989-8111-07-4
AU - Danger R.
AU - Berlanga R.
PY - 2007
SP - 13
EP - 20
DO - 10.5220/0001332200130020