Extracting Justifications from BioPortal Ontologies

  • Matthew Horridge
  • Bijan Parsia
  • Ulrike Sattler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7650)


This paper presents an evaluation of state of the art black box justification finding algorithms on the NCBO BioPortal ontology corpus. This corpus represents a set of naturally occurring ontologies that vary greatly in size and expressivity. The results paint a picture of the performance that can be expected when finding all justifications for entailments using black box justification finding techniques. The results also show that many naturally occurring ontologies exhibit a rich justificatory structure, with some ontologies having extremely high numbers of justifications per entailment.


Biomedical Ontology Model Base Diagnosis Cell Line Ontology Entailment Check Ontology Document 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Matthew Horridge
    • 1
  • Bijan Parsia
    • 2
  • Ulrike Sattler
    • 2
  1. 1.Stanford UniversityUSA
  2. 2.The University of ManchesterManchesterUK

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