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Link to original content: https://doi.org/10.1007/s11704-008-0030-y
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Dynamic description logic model for data integration

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Abstract

Data integration is the issue of retrieving and combining data residing at distributed and heterogeneous sources, and of providing users with transparent access without being aware of the details of the sources. Data integration is a very important issue because it deals with data infrastructure issues of coordinated computing systems. Despite its importance, the following key challenges make data integration one of the longest standing problems around: 1) how to solve the system heterogeneity; 2) how to build a global model; 3) how to process queries automatically and correctly; and 4) how to solve semantic heterogeneity.

This paper presents an extended dynamic description logic language to describe systems with dynamic actions. By this language, a universal and unified model for relational database systems and a model for data integration are presented. This paper presents a universal and unified description logic model for relational databases. The model is universal because any relational database system can be automatically transformed to the model; it is unified because it integrates three essential components of relational databases together: description logic knowledge bases modeling the relational data, atomic modalities modeling the atomic relational operations, and combined modalities modeling the combined relational operations-queries.

Furthermore, a description logic model for data integration is proposed which contains four layers of ontologies. Based on the model, a solution for each key challenge is proposed: a universal model eliminates system heterogeneity; a novel global model including three ontologies is proposed with some important benefits; a query process mechanism is provided by which user queries can be decomposed to queries over the sources; and for solving the semantic heterogeneity, this paper provides a framework under which semantic relations can be expressed and inferred.

In summary, this paper presents a dynamic knowledge base framework by an extended description logic language. Under the framework, databases and data integration systems are modeled, the query processing problem is converted into a semantic-preserving rewriting problem, and many other issues of data integration can be formally studied.

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References

  1. Arens Y, Knoblock C A, Shen W-M. Query reformulation for dynamic information integration. Journal Intelligent Information Systems, 1996, 6(2–3): 99–130

    Article  Google Scholar 

  2. Lenzerini M. Data integration: A theoretical perspective. In: Popa L, ed. PODS. ACM, 2002, 233–246

  3. Ullman J D. Information integration using logical views. In: Afrati F N, Kolaitis P G, eds. ICDT, Lecture Notes in Computer Science, Vol 1186. Berlin: Springer, 1997, 19–40

    Google Scholar 

  4. Cali A, Calvanese D, Giacomo G D, et al. Accessing data integration systems through conceptual schemas. In: Kunii H S, Jajodia S, Solvberg A, eds, ER, Lecture Notes in Computer Science, Vol 2224. Berlin: Springer, 2001, 270–284

    Google Scholar 

  5. Halevy A Y. Data integration: A status report. In: Weikum G, Schoning H, Rahm E, eds, BTW, LNI. GI, Vol 26, 2003, 24–29

  6. Halevy A Y, Rajaraman A, Ordille J J. Data integration: The teenage years. In: Dayal U, Whang K-Y, Lomet D B, et al, eds, VLDB. ACM, 2006, 9–16

  7. Wache H, Vogele T, Visser U, et al. Ontology-based integration of information-a survey of existing approaches. In: IJCAI, 2001, 108–117

  8. Keim D A, Kriegel H-P, Miethsam A. Integration of relational databases in a multidatabase system based on schema enrichment. In: RIDE-IMS, 1993, 96–104

  9. Levy A Y. Logic-based techniques in data integration. In: Minker J, ed, Workshop on Logic-Based Artificial Intelligence, Maryland: College Park, 1999

    Google Scholar 

  10. Halevy A Y. Theory of answering queries using views. SIGMOD Record, 2000, 29(4): 40–47

    Article  Google Scholar 

  11. Ullman J D, Widom J. A First Course in Database Systems. Prentice Hall, Inc, 1997

  12. Beeri C, Levy A Y, Rousset M-C. Rewriting queries using views in description logics. In: PODS, 1997, 99–108

  13. Calvanese D, Giacomo G D, Lenzerini M. Answering queries using views over description logics knowledge bases. In: AAAI/IAAI, 2000, 386–391

  14. Baader F, Calvanese D, McGuinness D L, et al, eds. The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge: Cambridge University Press, 2003

    MATH  Google Scholar 

  15. Borgida A. Description logics in data management. IEEE Trans Knowl Data Eng, 1995, 7(5): 671–682

    Article  Google Scholar 

  16. Calvanese D, Giacomo G D, Lenzerini M. Description logics for information integration. In: Computational Logic: Logic Programming and Beyond, 2002, 41–60

  17. Calvanese D, Lenzerini M, Nardi D. Description logics for conceptual data modelling. In: Chomicki J, Saake G, eds. Logic for Databases and Information systems. Holland: Kluwer, 1998, 229–263

    Google Scholar 

  18. Wolter F, Zakharyaschev M. Dynamic description logics. In: Zakharyaschev M, Segerberg K, de Rijke M, et al, eds. Advances in Modal Logic. CSLI Publications, 1998, 431–446

  19. Calvanese D, Lenzerini M, Nardi D. Unifying class-based representation formalisms. Journal of Artificial Intelligence Research, 1999, 11: 199–240

    MATH  MathSciNet  Google Scholar 

  20. Sa S, Wang S. Introductions of Database Systems. 3rd ed. Beijing: Higher Education Press, 2003 (in Chinese)

    Google Scholar 

  21. Grun G A. Description logics. Available at: http://www.cs.sfu.ca/people/GradStudents/grun/ personal/s1.ps, 1998

  22. Chomicki J, Saake G, eds. Logics for Databases and Information Systems (the book grows out of the Dagstuhl Seminar 9529: Role of Logics in Information Systems, 1995). Holland: Kluwer, 1998

    Google Scholar 

  23. Emerson E A. Temporal and modal logic. In: Handbook of Theoretical Computer Science, Volume B: Formal Models and Sematics. Amsterdam: Elsevier and MIT Press, 1990, 995–1072

    Google Scholar 

  24. Wolter F, Zakharyaschev M. Modal description logics: Modalizing roles. Fundam Inform, 1999, 39(4): 411–438

    MATH  MathSciNet  Google Scholar 

  25. Rosen K H. Discrete Mathematics and Its Applications. New York: McGraw-Hill, Inc, 1996

    Google Scholar 

  26. Calvanese D, Giacomo G D, Lenzerini M. Representing and reasoning on xml documents: A description logic approach. Journal of Logic and Computation, 1999, 9(3): 295–318

    Article  MATH  MathSciNet  Google Scholar 

  27. Papakonstantinou Y, Gupta A, Garcia-Molina H, et al. A query translation scheme for rapid implementation of wrappers. In: Ling T W, Mendelzon A O, Vieille L, eds, DOOD, Lecture Notes in Computer Science, Vol 1013. Berlin: Springer, 1995, 161–186

    Google Scholar 

  28. Jean S, Ameur Y A, Pierra G. Querying ontology based database using ontoql (an ontology query language). In: Meersman R, Tari Z, eds, OTM Conferences, Lecture Notes in Computer Science, Vol 4275. Berlin: Springer, 2006, 704–721

    Google Scholar 

  29. Calvanese D, Giacomo G D, Lenzerini M. A framework for ontology integration. In: Cruz I F, Decker S, Euzenat J, et al, eds, SWWS, 2001, 303–316

  30. Ehrig M, Sure Y. Ontology mapping — an integrated approach. In: Bussler C, Davies J, Fensel D, et al, eds, ESWS, Lecture Notes in Computer Science, Vol 3053, Berlin: Springer, 2004, 76–91

    Google Scholar 

  31. Kalfoglou Y, Schorlemmer W M. Ontology mapping: The state of the art. In: Kalfoglou Y, Schorlemmer W M, Sheth A P, et al, eds, Semantic Interoperability and Integration, volume 04391 of Dagstuhl Seminar Proceedings. IBFI, Schloss Dagstuhl, Germany, 2005

  32. Madhavan J, Bernstein P A, Domingos P, et al. Representing and reasoning about mappings between domain models. In: AAAI/IAAI, 2002, 80–86

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Correspondence to Guoshun Hao.

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Hao, G., Ma, S., Sui, Y. et al. Dynamic description logic model for data integration. Front. Comput. Sci. China 2, 306–330 (2008). https://doi.org/10.1007/s11704-008-0030-y

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