Earth Science Informatics

, Volume 7, Issue 4, pp 249–264 | Cite as

SWEET ontology coverage for earth system sciences

  • Nicholas DiGiuseppe
  • Line C. Pouchard
  • Natalya F. Noy
Research Article

Abstract

Scientists in the Earth and Environmental Sciences (EES) domain increasingly use ontologies to analyze and integrate their data. For example, the NASA’s SWEET ontologies (Semantic Web for Earth and Environmental Terminology) have become the de facto standard ontologies to represent the EES domain formally (Raskin 2010). Now we must develop principled ways both to evaluate existing ontologies and to ascertain their quality in a quantitative manner. Existing literature describes many potential quality metrics for ontologies. Among these metrics is the coverage metric, which approximates the relevancy of an ontology to a corpus (Yao et al. (PLoS Comput Biol 7(1):e1001055+, 2011)). This paper has three primary contributions to the EES domain: (1) we present an investigation of the applicability of existing coverage techniques for the EES domain; (2) we present a novel expansion of existing techniques that uses thesauri to generate equivalence and subclass axioms automatically; and (3) we present an experiment to establish an upper-bound coverage expectation for the SWEET ontologies against real-world EES corpora from DataONE (Michener et al. (Ecol Inform 11:5–15, 2012)), and a corpus designed from research articles to specifically match the topics covered by the SWEET ontologies. This initial evaluation suggests that the SWEET ontology can accurately represent real corpora within the EES domain.

Keywords

Ontology Ontology coverage Semantic web Empirical 

Notes

Acknowledgments

This material is based upon work supported by the National Science Foundation, through Award CCF-1116943 and through Graduate Research Fellowship under Grant No. DGE-0808392. Michael Huhns was extremely helpful in directing and crystalizing this research. We would also like to thank Andrey Rzhetsky for providing the seven thesauri used in our experiment.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Nicholas DiGiuseppe
    • 1
  • Line C. Pouchard
    • 2
  • Natalya F. Noy
    • 3
  1. 1.University of California, IrvineIrvineUSA
  2. 2.Oak Ridge National LaboratoryOak RidgeUSA
  3. 3.Stanford Center for Biomedical Informatics ResearchStanford UniversityStanfordUSA

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