Skip to main content

An Approach to Detect Collaborative Conflicts for Ontology Development

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5446))

Abstract

Ontology has been widely adopted as the basis of knowledge sharing and knowledge-based public services. However, ontology construction is a big challenge, especially in collaborative ontology development, in which conflicts are often a problem. Traditional collaborative methods are suitable for centralized teamwork only, and are ineffective if the ontology is developed and maintained by mass broadly distributed participators lacking communications. In this kind of highly collaborative ontology development, automated conflicts detection is essential. In this paper, we propose an approach to classify and detect collaborative conflicts according to some mechanisms: 1) impact range of a revision, 2) semantic rules, and 3) heuristic similarity measures. Also we present a high effective detecting algorithm with evaluation.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Noy, N.F., Chugh, A., Alani, H.: The CKC Challenge: Exploring Tools for Collaborative Knowledge Construction. IEEE Intelligent Systems 23(1), 64–68 (2008)

    Article  Google Scholar 

  2. Horrocks, Sattler, U., Tobies, S.: Practical reasoning for expressive description logics. In: Ganzinger, H., McAllester, D., Voronkov, A. (eds.) LPAR 1999. LNCS, vol. 1705. Springer, Heidelberg (1999)

    Google Scholar 

  3. Auer, S., Dietzold, S., Riechert, T.: OntoWiki – A tool for social, semantic collaboration. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 736–749. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  4. Haase, P., Stojanovic, L.: Consistent evolution of OWL ontologies. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 182–197. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  5. Bozsak, E., et al.: KAON - towards a large scale semantic web. In: Bauknecht, K., Tjoa, A.M., Quirchmayr, G. (eds.) EC-Web 2002. LNCS, vol. 2455, p. 304. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  6. Madhavan, J., Bernstein, P.A., Rahm, E.: Generic Schema Matching with Cupid. In: Proc. VLDB Conf., pp. 49–58 (September 2001)

    Google Scholar 

  7. Sure, Y., Erdmann, M., Angele, J., Staab, S., Studer, R., Wenke, D.: OntoEdit: Collaborative ontology development for the semantic web. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, p. 221. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  8. Noy, N.F., Sintek, M., Decker, S., Crubezy, M., Fergerson, R.W., Musen, M.A.: Creating Semantic Web Contents with Protege 2000. IEEE Intelligent Systems 16(2), 60–71 (2001)

    Article  Google Scholar 

  9. Web—ontology working group. OWL Web ontology Language Overview, http://www.w3.org/TR/2003/PR-owl-features-20031215

  10. Hwang, S.-H., Kim, H.-G., Yang, H.-S.: A FCA-based ontology construction for the design of class hierarchy. In: Gervasi, O., Gavrilova, M.L., Kumar, V., Laganá, A., Lee, H.P., Mun, Y., Taniar, D., Tan, C.J.K. (eds.) ICCSA 2005. LNCS, vol. 3482, pp. 827–835. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  11. Ram, S., Park, J.: Semantic conflict resolution ontology (SCROL): an ontology for detecting and resolving data and schema-level semantic conflicts. IEEE Transactions on Knowledge and Data Engineering 16(2) (February 2004)

    Google Scholar 

  12. Bechhofer, S., Horrocks, I., Goble, C., Stevens, R.: OilEd: A reason-able ontology editor for the semantic web. In: Baader, F., Brewka, G., Eiter, T. (eds.) KI 2001. LNCS, vol. 2174, p. 396. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chen, Y., Peng, X., Zhao, W. (2009). An Approach to Detect Collaborative Conflicts for Ontology Development. In: Li, Q., Feng, L., Pei, J., Wang, S.X., Zhou, X., Zhu, QM. (eds) Advances in Data and Web Management. APWeb WAIM 2009 2009. Lecture Notes in Computer Science, vol 5446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00672-2_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-00672-2_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00671-5

  • Online ISBN: 978-3-642-00672-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics