[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Ontology-Based Mediation with Quality Criteria

  • Conference paper
  • First Online:
Business Intelligence (CBI 2023)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 484 ))

Included in the following conference series:

  • 321 Accesses

Abstract

Information integration has a long history since humans started using and collecting information. But, it has been a strong focus of IT research since many recent years. It deals with providing a unified and transparent access to a collection of heterogeneous data sources. In information integration, the formulization of a global schema is a difficult task that manages multiple, autonomous and heterogeneous data sources. This paper presents a semantic system named OntMed for an ontology-based data integration of heterogeneous data sources to achieve interoperability between them. Our system is based on the quality criteria (consistency, completeness and conciseness) for building the reliable analysis contexts to provide an accurate unified view of data to the end user. The generation of an error-free global analysis context with the semantic validation of initial mappings generates accuracy, and provides the means to access and exchange information in semantically sound manner. In addition, data integration in this way becomes more practical for dynamic situations and helps decision makers to work within a more consistent and reliable virtual data warehouse.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 43.99
Price includes VAT (United Kingdom)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
GBP 54.99
Price includes VAT (United Kingdom)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://oaei.ontologymatching.org/2015/oa4qa/results.html.

References

  1. Bernstein, P.A., Haas, L.M.: Information integration in the enterprise. Commun. ACM (CACM) 51(1), 72–79 (2008)

    Article  Google Scholar 

  2. Ziegler, P., Dittrich, K.R.: Three Decades of Data Integration - All Problems Solved?, WCC, pp. 3–12 (2004)

    Google Scholar 

  3. IDC, Worldwide Data Integration and Access Software, 2008–2012, Forecast. Doc No. 211636, Apr. (2008)

    Google Scholar 

  4. Wache, H., et al.: Ontology-based integration of information - a survey of existing approaches. In: Proceedings of the IJCAI-01 Workshop on Ontologies and Information Sharing (2001)

    Google Scholar 

  5. Arens, Y., Knoblock, C.A., Hsu, C.: Query Processing in the SIMS Information Mediator. In The AAAI Press (1996)

    Google Scholar 

  6. Mena, E., Kashyap, V., Sheth, A.P., Illarramendi, A.: OBSERVER: an approach for query processing in global information systems based on interoperation across pre-existing ontologies. In: Proceedings of the 1st IFCIS International Conference on Cooperative Information Systems (CoopIS 1996), pp. 14–25 (1996)

    Google Scholar 

  7. Cruz, I.F., Xiao, H.: Using a layered approach for interoperability on the semantic web. In: Proceedings of the 4th International Conference on Web Information Systems Engineering (WISE), pp. 221–232, Rome, Italy (2003)

    Google Scholar 

  8. Lenzerini, M.: Data Integration: A Theoretical Perspective. PODS, pp. 233–246 (2002)

    Google Scholar 

  9. Chaudhuri, S., Dayal, U.: An overview of data warehousing and OLAP technology, ACM SIGMOD Record 26(1), 65–74 (1997)

    Google Scholar 

  10. Inmon, W.H.: Building the Data Warehouse. John Wiley & Sons Inc, New York, USA (1992)

    Google Scholar 

  11. Kimball, R.: The operational data warehouse. DBMS 11(1), 14–16 (1998)

    Google Scholar 

  12. Fahad, M., Qadir, M.A.: A framework for ontology evaluation. 16th ICCS Supplement Proceeding, 354, pp.149–158, France (2008)

    Google Scholar 

  13. Maiz, N., Fahad, M., Boussaid, O., Tayab, F.B.: Automatic ontology merging by hierarchical clustering and inference mechanisms. In: proceedings of 10th International Conference on knowledge Management and Knowledge Technologies (I-Know’10), Sept 1–3, Messe Congress Graz, Austria (2010)

    Google Scholar 

  14. Upadhyaya, S.R., Kumar, P.S.: ERONTO: a tool for extracting ontologies from extended E/R diagrams. ACM Symposium on Applied Computing (2005)

    Google Scholar 

  15. Xu, Z., Zhang, S., Dong, Y.: Mapping between relational database schema and OWL ontology for Deep Annotation. In: Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI’06), IEEE (2006)

    Google Scholar 

  16. Fahad, M., Moalla, N., Bouras, A.: Detection and resolution of semantic inconsistency and redundancy in an automatic ontology merging system. J. Intell. Inf. Syst. (JIIS) 39(2), 535–557 (2012)

    Article  Google Scholar 

  17. Gómez-Pérez, A.: Evaluating ontologies: cases of study. IEEE Intell. Syst. and their Appl. 16(3), 391–409 (2001)

    MATH  Google Scholar 

  18. Gomez-Perez, A., Fernández-López, M., Corcho, O.: Ontological engineering: with examples from the areas of knowledge management. E-Commerce and the Semantic Web. Springer, London (2004). https://doi.org/10.1007/b97353

  19. Baumeister, J., Seipel, D.S.: Smelly owls–design anomalies in ontologies. In: 18th Intl. Florida AI Research Society Conference, pp. 251–220. AAAI Press (2005)

    Google Scholar 

  20. Fahad, M.: Initial results for ontology matching workshop 2015, DKP-AOM: Results for OAEI 2015. In: CEUR Workshop Proceedings 1766, pp. 82–96. 5 (2015). http://oaei.ontologymatching.org/2015/conference/index.html

  21. Cheatham, M., Dragisic, Z., Euzenat, J., Faria, D., Ferrara, A., et al.: Results of the ontology alignment evaluation initiative 2015. 10th ISWC Workshop on Ontology Matching (OM), Oct, Bethlehem, United States. pp. 60–115 (2015)

    Google Scholar 

  22. Solimando, A., Jiménez-Ruiz, E., Guerrini, G.: Detecting and correcting conservativity principle violations in ontology-to-ontology mappings. In: Mika, P., et al. (eds.) ISWC 2014. LNCS, vol. 8797, pp. 1–16. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11915-1_1

    Chapter  Google Scholar 

  23. Solimando, A., Jimenez-Ruiz, E., Pinkel, C.: Evaluating ontology alignment systems in query answering tasks. Poster paper at International Semantic Web Conference (ISWC) (2014)

    Google Scholar 

  24. Kaur, P., Kaur, P.: New approach of computing data cubes in data warehousing. Int. J. Inf. Comp. Technol. 4(14), 1411–1417 (2014)

    Google Scholar 

  25. Chen, Z., Zhao, T.: A cube model approach for data warehouse. Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering, pp. 846–849 (2015)

    Google Scholar 

  26. Liu, Y., Sung, S.Y., Xiong, H.: A cubic-wise balance approach for privacy preservation in data cubes. Inf. Sci. 176, 1215–1240 (2006)

    Article  MATH  Google Scholar 

  27. Alejandro, G.T., Marotta, A.: An Overview of Data Warehouse Design Approaches and Techniques (2001)

    Google Scholar 

  28. Huang, S., Chou, T., Seng, J.: Data warehouse enhancement: a semantic cube model approach. Inf. Sci. 177(11), 2238–2254 (2007)

    Article  Google Scholar 

  29. Sobral, T., Galvão, T., Borges, J.: An ontology-based approach to knowledge-assisted integration and visualization of urban mobility data. Expert Systems with Applications, 150 (2020)

    Google Scholar 

  30. Belitz-Hellwich, W.: An Ontology-Based Platform for Information Integration; Supporting Sustainable Smart Transportation Infrastructure (2023). https://www.diva-portal.org/smash/get/diva2:1737543/FULLTEXT01.pdf

  31. Haw, S.-C., May, J.-W., Subramaniam, S.: Mapping relational databases to ontology representation: a review. In: ICDTE’17, pp. 54–55 (2017)

    Google Scholar 

  32. Kharlamov, E., Hovland, D., Jimenez-Rui, E., et al.: Ontology based data access in statoil. J. Web Semantics 44, 3–36 (2017)

    Article  Google Scholar 

  33. Can, O., Unalir, M.: Revisiting ontology based access control: the case for ontology based data access. In: Proceedings of the 8th International Conference on Information Systems Security and Privacy (ICISSP), pp. 515–518 (2022)

    Google Scholar 

Download references

Acknowledgement

The research depicted in this paper is funded by the French National Research Agency (ANR), project ANR-19-CE23–0005 BI4people (Business Intelligence for the people).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Muhammad Fahad .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Fahad, M. (2023). Ontology-Based Mediation with Quality Criteria. In: El Ayachi, R., Fakir, M., Baslam, M. (eds) Business Intelligence. CBI 2023. Lecture Notes in Business Information Processing, vol 484 . Springer, Cham. https://doi.org/10.1007/978-3-031-37872-0_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-37872-0_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-37871-3

  • Online ISBN: 978-3-031-37872-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics