Advertisement

A Flexible Framework for Understanding the Dynamics of Evolving RDF Datasets

  • Yannis RoussakisEmail author
  • Ioannis Chrysakis
  • Kostas Stefanidis
  • Giorgos Flouris
  • Yannis Stavrakas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9366)

Abstract

The dynamic nature of Web data gives rise to a multitude of problems related to the description and analysis of the evolution of RDF datasets, which are important to a large number of users and domains, such as, the curators of biological information where changes are constant and interrelated. In this paper, we propose a framework that enables identifying, analysing and understanding these dynamics. Our approach is flexible enough to capture the peculiarities and needs of different applications on dynamic data, while being formally robust due to the satisfaction of the completeness and unambiguity properties. In addition, our framework allows the persistent representation of the detected changes between versions, in a manner that enables easy and efficient navigation among versions, automated processing and analysis of changes, cross-snapshot queries (spanning across different versions), as well as queries involving both changes and data. Our work is evaluated using real Linked Open Data, and exhibits good scalability properties.

Keywords

Change Detection Complex Change Simple Change SPARQL Query Triple Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Arenas, M., Gutierrez, C., Pérez, J.: On the semantics of SPARQL. In: Semantic Web Information Management - A Model-Based Perspective. Springer (2009)Google Scholar
  2. 2.
    Auer, S., Herre, H.: A versioning and evolution framework for RDF knowledge bases. In: Virbitskaite, I., Voronkov, A. (eds.) PSI 2006. LNCS, vol. 4378, pp. 55–69. Springer, Heidelberg (2007) CrossRefGoogle Scholar
  3. 3.
    Cloran, R., Irvin, B.: Transmitting RDF graph deltas for a cheaper semantic web. In: SATNAC (2005)Google Scholar
  4. 4.
    Franconi, E., Meyer, T., Varzinczak, I.: Semantic diff as the basis for knowledge base versioning. In: NMR (2010)Google Scholar
  5. 5.
    Galani, T., Stavrakas, Y., Papastefanatos, G., Flouris, G.: Supporting complex changes in RDF(S) knowledge bases. In: MEPDaW-15 (2015)Google Scholar
  6. 6.
    Gröner, G., Silva Parreiras, F., Staab, S.: Semantic recognition of ontology refactoring. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part I. LNCS, vol. 6496, pp. 273–288. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  7. 7.
    Hartmann, J., Palma, R., Sure, Y., Haase, P., Suarez-Figueroa, M.C.: OMV ontology metadata vocabulary. In: Ontology Patterns for the Semantic Web Workshop (2005)Google Scholar
  8. 8.
    Im, D.-H., Lee, S.-W., Kim, H.-J.: Backward inference and pruning for RDF change detection using RDBMS. J. Information Science 39(2), 238–255 (2013)CrossRefGoogle Scholar
  9. 9.
    Klein, M., Proefschrift, A., Christiaan, M., Klein, A., Akkermans, J.M.: Change management for distributed ontologies. Technical report, VU University Amsterdam (2004)Google Scholar
  10. 10.
    Konev, B., Walther, D., Wolter, F.: The logical difference problem for description logic terminologies. In: Armando, A., Baumgartner, P., Dowek, G. (eds.) IJCAR 2008. LNCS (LNAI), vol. 5195, pp. 259–274. Springer, Heidelberg (2008) CrossRefGoogle Scholar
  11. 11.
    Kontchakov, R., Wolter, F., Zakharyaschev, M.: Can you tell the difference between DL-lite ontologies? In: KR (2008)Google Scholar
  12. 12.
    Lee, D.-H., Im, D.-H., Kim, H.-J.: A change detection technique for RDF documents containing nested blank nodes. In: PSI (2007)Google Scholar
  13. 13.
    Noy, N.F., Chugh, A., Liu, W., Musen, M.A.: A framework for ontology evolution in collaborative environments. 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. 544–558. Springer, Heidelberg (2006) CrossRefGoogle Scholar
  14. 14.
    Noy, N.F., Musen, M.A.: Promptdiff: a fixed-point algorithm for comparing ontology versions. In: AI (2002)Google Scholar
  15. 15.
    Papavasileiou, V., Flouris, G., Fundulaki, I., Kotzinos, D., Christophides, V.: High-level change detection in RDF(S) KBs. ACM Trans. Database Syst., 38(1) (2013)Google Scholar
  16. 16.
    Pérez, J., Arenas, M., Gutierrez, C.: Semantics and complexity of SPARQL. 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. 30–43. Springer, Heidelberg (2006) CrossRefGoogle Scholar
  17. 17.
    Plessers, P., De Troyer, O., Casteleyn, S.: Understanding ontology evolution: A change detection approach. Web Semant. 5(1), 39–49 (2007)CrossRefGoogle Scholar
  18. 18.
    Prud’hommeaux, E., Harris, S., Seaborne, A.: SPARQL 1.1 Query Language. Technical report, W3C (2013)Google Scholar
  19. 19.
    Rieß, C., Heino, N., Tramp, S., Auer, S.: EvoPat – pattern-based evolution and refactoring of RDF knowledge bases. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part I. LNCS, vol. 6496, pp. 647–662. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  20. 20.
    Roussakis, Y., Chrysakis, I., Stefanidis, K., Flouris, G.: A flexible framework for understanding the dynamics of evolving RDF sdatasets: Extended version. Technical Report TR-456, FORTH-ICS, July 2015Google Scholar
  21. 21.
    Stefanidis, K., Chrysakis, I., Flouris, G.: On designing archiving policies for evolving rdf datasets on the web. In: Yu, E., Dobbie, G., Jarke, M., Purao, S. (eds.) ER 2014. LNCS, vol. 8824, pp. 43–56. Springer, Heidelberg (2014) Google Scholar
  22. 22.
    Stefanidis, K., Efthymiou, V., Herchel, M., Christophides, V.: Entity resolution in the web of data. In: WWW (2014)Google Scholar
  23. 23.
    Umbrich, J., Hausenblas, M., Hogan, A., Polleres, A., Decker, S.: Towards dataset dynamics: change frequency of linked open data sources. In: LDOW (2010)Google Scholar
  24. 24.
    Zeginis, D., Tzitzikas, Y., Christophides, V.: On computing deltas of RDF/S knowledge bases. ACM Trans. Web 5(3), 14:1–14:36 (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Yannis Roussakis
    • 1
    Email author
  • Ioannis Chrysakis
    • 1
  • Kostas Stefanidis
    • 1
  • Giorgos Flouris
    • 1
  • Yannis Stavrakas
    • 2
  1. 1.Institute of Computer ScienceFORTHHeraklionGreece
  2. 2.Institute for the Management of Information SystemsATHENAAthensGreece

Personalised recommendations