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Analyzing the Evolution of Linked Vocabularies

  • Mohammad Abdel-QaderEmail author
  • Iacopo Vagliano
  • Ansgar Scherp
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11496)

Abstract

Reusing terms results in a Network of Linked vOcabularies (NeLO), where the nodes are the vocabularies that use at least one term from some other vocabulary and thus depend on each other. These dependencies become a problem when vocabularies in the network change, e. g., when terms are deprecated or deleted. In these cases, all dependent vocabularies in the network need to be updated. So far, there has been no study that analyzes vocabulary changes in NeLO over time. To address this shortcoming, we compute the state of NeLO from the available versions of the vocabularies over 17 years. We analyze static parameters of NeLO such as its size, density, average degree, and the most important vocabularies at certain points in time. We further investigate how NeLO changes over time. Specifically, we measure the impact of a change in one vocabulary to others, how the reuse of terms changes, and the importance of vocabularies changes. Our analyses provide for the first time in-depth insights into the structure and evolution of NeLO. This study helps ontology engineers to identify shortcomings of the data modeling and to assess the dependencies implied with reusing a specific vocabulary.

Notes

Acknowledgment

This work was supported by the DFG (German Research Foundation) with the LOC-DB project (Grants No. GZ:SCHE 1687/5-1) and the EU’s Horizon 2020 programme under grant agreement H2020-693092 MOVING.

References

  1. 1.
    Abdel-Qader, M., Scherp, A., Vagliano, I.: Analyzing the evolution of vocabulary terms and their impact on the LOD cloud. In: Gangemi, A., et al. (eds.) ESWC 2018. LNCS, vol. 10843, pp. 1–16. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-93417-4_1CrossRefGoogle Scholar
  2. 2.
    Cardoso, S.D., et al.: Leveraging the impact of ontology evolution on semantic annotations. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds.) EKAW 2016. LNCS (LNAI), vol. 10024, pp. 68–82. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-49004-5_5CrossRefGoogle Scholar
  3. 3.
    Dividino, R., Gottron, T., Scherp, A.: Strategies for efficiently keeping local linked open data caches up-to-date. In: Arenas, M., et al. (eds.) ISWC 2015, Part II. LNCS, vol. 9367, pp. 356–373. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-25010-6_24CrossRefGoogle Scholar
  4. 4.
    Dos Reis, J.C., Pruski, C., Da Silveira, M., Reynaud-Delaître, C.: Understanding semantic mapping evolution by observing changes in biomedical ontologies. J. Biomed. Inform. 47, 71–82 (2014)CrossRefGoogle Scholar
  5. 5.
    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., et al. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 229–242. Springer, Heidelberg (2009).  https://doi.org/10.1007/978-3-642-04930-9_15CrossRefGoogle Scholar
  6. 6.
    Gottron, T., Gottron, C.: Perplexity of index models over evolving linked data. In: Presutti, V., et al. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 161–175. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-07443-6_12CrossRefGoogle Scholar
  7. 7.
    Hartung, M., Kirsten, T., Rahm, E.: Analyzing the evolution of life science ontologies and mappings. In: Bairoch, A., Cohen-Boulakia, S., Froidevaux, C. (eds.) DILS 2008. LNCS, vol. 5109, pp. 11–27. Springer, Heidelberg (2008).  https://doi.org/10.1007/978-3-540-69828-9_4CrossRefGoogle Scholar
  8. 8.
    Janik, M., Scherp, A., Staab, S.: The semantic web: collective intelligence on the web. Inform. Spektrum 34(5), 469 (2011)CrossRefGoogle Scholar
  9. 9.
    Jiménez-Ruiz, E., Grau, B.C., Sattler, U., Schneider, T., Berlanga, R.: Safe and economic re-use of ontologies: a logic-based methodology and tool support. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 185–199. Springer, Heidelberg (2008).  https://doi.org/10.1007/978-3-540-68234-9_16CrossRefGoogle Scholar
  10. 10.
    Käfer, T., Abdelrahman, A., Umbrich, J., O’Byrne, P., Hogan, A.: Observing linked data dynamics. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 213–227. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-38288-8_15CrossRefGoogle Scholar
  11. 11.
    Kamdar, M.R., Tudorache, T., Musen, M.A.: A systematic analysis of term reuse and term overlap across biomedical ontologies. Semantic web 8(6), 853–871 (2017)CrossRefGoogle Scholar
  12. 12.
    Meusel, R., Bizer, C., Paulheim, H.: A web-scale study of the adoption and evolution of the schema.org vocabulary over time. In: International Conference on Web Intelligence, Mining and Semantics, p. 15. ACM (2015)Google Scholar
  13. 13.
    Nishioka, C., Scherp, A.: Temporal patterns and periodicity of entity dynamics in the Linked Open Data Cloud. In: K-CAP, p. 22. ACM (2015)Google Scholar
  14. 14.
    Noura, M., Gyrard, A., Heil, S., Gaedke, M.: Concept extraction from the web of things knowledge bases. In: The International Conference WWW/Internet (2018)Google Scholar
  15. 15.
    Palma, R., Zablith, F., Haase, P., Corcho, O.: Ontology evolution. In: Suárez-Figueroa, M.C., Gómez-Pérez, A., Motta, E., Gangemi, A. (eds.) Ontology Engineering in a Networked World, pp. 235–255. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-24794-1_11CrossRefGoogle Scholar
  16. 16.
    Papakonstantinou, V., Fundulaki, I., Flouris, G.: Assessing linked data versioning systems: the semantic publishing versioning benchmark. In: International Workshop on Scalable Semantic Web Knowledge Base Systems@ISWC, pp. 219–234 (2018)Google Scholar
  17. 17.
    Schaible, J., Gottron, T., Scherp, A.: TermPicker: enabling the reuse of vocabulary terms by exploiting data from the Linked Open Data Cloud. In: Sack, H., Blomqvist, E., d’Aquin, M., Ghidini, C., Ponzetto, S.P., Lange, C. (eds.) ESWC 2016. LNCS, vol. 9678, pp. 101–117. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-34129-3_7CrossRefGoogle Scholar
  18. 18.
    Vandenbussche, P.Y., Atemezing, G.A., Poveda-Villalón, M., Vatant, B.: Linked Open Vocabularies (LOV): a gateway to reusable semantic vocabularies on the web. Semantic Web 8(3), 437–452 (2017)CrossRefGoogle Scholar
  19. 19.
    Zaki, M.J., Meira Jr., W., Meira, W.: Data Mining and Analysis: Fundamental Concepts and Algorithms. Cambridge University Press, Cambridge (2014)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Christian-Albrechts UniversityKielGermany
  2. 2.ZBW – Leibniz Information Centre for EconomicsKielGermany
  3. 3.University of EssexColchesterUK

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