Selection and Combination of Heterogeneous Mappings to Enhance Biomedical Ontology Matching

  • Amina AnnaneEmail author
  • Zohra Bellahsene
  • Faiçal Azouaou
  • Clement Jonquet
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10024)


This paper presents a novel background knowledge approach which selects and combines existing mappings from a given biomedical ontology repository to improve ontology alignment. Current background knowledge approaches usually select either manually or automatically a limited number of different ontologies and use them as a whole for background knowledge. Whereas in our approach, we propose to pick up only relevant concepts and relevant existing mappings linking these concepts all together in a specific and customized background knowledge graph. Paths within this graph will help to discover new mappings. We have implemented and evaluated our approach using the content of the NCBO BioPortal repository and the Anatomy benchmark from the Ontology Alignment Evaluation Initiative. We used the mapping gain measure to assess how much our final background knowledge graph improves results of state-of-the-art alignment systems. Furthermore, the evaluation shows that our approach produces a high quality alignment and discovers mappings that have not been found by state-of-the-art systems.


Ontology matching Background knowledge Repository of ontologies Biomedical ontologies BioPortal 



This work was achieved during a LIRMM-ESI collaboration within the SIFR project funded in part by the French National Research Agency (grant ANR-12-JS02-01001), as well as by University of Montpellier, the CNRS and the EU H2020 MSCA program.


  1. 1.
    Aleksovski, Z., Kate, W.T., Van Harmelen, F.: Exploiting the structure of background knowledge used. In: 1st International Conference on Ontology Matching, vol. 225, pp. 13–24 (2006)Google Scholar
  2. 2.
    Annane, A., Emonet, V., Azouaou, F., Jonquet, C.: Multilingual mapping reconciliation between english-french biomedical ontologies. In: 6th International Conference on Web Intelligence, Mining, Semantics, WIMS, pp. 13:1–13:12 (2016)Google Scholar
  3. 3.
    Bodenreider, O.: The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res. 32, 267–270 (2004)CrossRefGoogle Scholar
  4. 4.
    Cheatham, M., et al.: Results of the ontology alignment evaluation initiative 2015. In: 10th ISWC Workshop on Ontology Matching, pp. 60–115 (2015)Google Scholar
  5. 5.
    Chen, X., Xia, W., Jiménez-Ruiz, E., Cross, V.V.: Extending an ontology alignment system with bioportal: a preliminary analysis. In: ISWC, pp. 313–316 (2014)Google Scholar
  6. 6.
    Smith, B., et al.: The OBO foundry: coordinated evolution of ontologies to support biomedical data integration. Nat. Biotechnol. 25(11), 1251–1255 (2007)CrossRefGoogle Scholar
  7. 7.
    Euzenat, J., Shvaiko, P.: Ontology Matching. Springer, Heidelberg (2013)CrossRefzbMATHGoogle Scholar
  8. 8.
    Faria, D., et al.: Automatic background knowledge selection for matching biomedical ontologies. PloS one 9(11), e111226 (2014)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Faria, D., Jiménez-Ruiz, E., Pesquita, C., Santos, E., Couto, F.M.: Towards annotating potential incoherences in bioportal mappings. In: Mika, P., et al. (eds.) ISWC 2014, Part II. LNCS, vol. 8797, pp. 17–32. Springer, Heidelberg (2014)Google Scholar
  10. 10.
    Ghazvinian, A., Noy, N.F., Musen, M.A.,et al.: Creating mappings for ontologies in biomedicine: simple methods work. In: AMIA, pp. 198–202 (2009)Google Scholar
  11. 11.
    Ghazvinian, A., Noy, N.F., Jonquet, C., Shah, N., Musen, M.A.: What four million mappings can tell you about two hundred ontologies. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 229–242. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  12. 12.
    Gross, A., Hartung, M., Kirsten, T., Rahm, E.: Mapping composition for matching large life science ontologies. In: ICBO, pp. 109–116 (2011)Google Scholar
  13. 13.
    Hartung, M., Gross, A., Kirsten, T., Rahm, E.: Effective mapping composition for biomedical ontologies. In: ESWC, pp. 176–190 (2012)Google Scholar
  14. 14.
    Jiménez-Ruiz, E., Grau, B.C., Solimando, A., Cross, V.V.: Logmap family results for OAEI 2015. In: 10th International Workshop on Ontology Matching, pp. 171–175 (2015)Google Scholar
  15. 15.
    Jonquet, C., Shah, N., Musen, M.: The open biomedical annotator. In: AMIA Summit on Translational Bioinformatics, pp. 56–60 (2009)Google Scholar
  16. 16.
    Locoro, A., David, J., Euzenat, J.: Context-based matching: design of a flexible framework and experiment. J. Data Semant. 3(1), 25–46 (2014)CrossRefGoogle Scholar
  17. 17.
    Mascardi, V., Locoro, A., Rosso, P.: Automatic ontology matching via upper ontologies: a systematic evaluation. IEEE Trans. Knowl. Data Eng. 22(5), 609–623 (2010)CrossRefGoogle Scholar
  18. 18.
    Quix, C., Roy, P., Kensche, D.: Automatic selection of background knowledge for ontology matching. In: International Workshop on Semantic Web Information Management, p. 5. ACM (2011)Google Scholar
  19. 19.
    Sabou, M., d’Aquin, M., Motta, E.: Exploring the semantic web as background knowledge for ontology matching. In: Spaccapietra, S., Pan, J.Z., Thiran, P., Halpin, T., Staab, S., Svatek, V., Shvaiko, P., Roddick, J. (eds.) Journal on Data Semantics XI. LNCS, vol. 5383, pp. 156–190. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  20. 20.
    Safar, B., Reynaud, C., Calvier, F.: Techniques d’alignement d’ontologies basées sur la structure dune ressource complémentaire. 1ères Journées Francophones sur les Ontologies, pp. 21–35 (2007)Google Scholar
  21. 21.
    Shvaiko, P., Euzenat, J.: Ontology matching: state of the art and future challenges. IEEE Trans. Knowl. Data Eng 25(1), 158–176 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Amina Annane
    • 1
    • 2
    Email author
  • Zohra Bellahsene
    • 1
  • Faiçal Azouaou
    • 2
  • Clement Jonquet
    • 1
    • 3
  1. 1.Université de Montpellier, Laboratoire d’Informatiquede Robotique et de Microélectronique (LIRMM)MontpellierFrance
  2. 2.Ecole Nationale Supérieure en Informatique (ESI)AlgiersAlgeria
  3. 3.Center for Biomedical Informatics ResearchStanford UniversityStanfordUSA

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