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Publishing a Disease Ontologies as Linked Data

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Semantic Technology (JIST 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8388))

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Abstract

Publishing open data as linked data is a significant trend in not only the Semantic Web community but also other domains such as life science, government, media, geographic research and publication. One feature of linked data is the instance-centric approach, which assumes that considerable linked instances can result in valuable knowledge. In the context of linked data, ontologies offer a common vocabulary and schema for RDF graphs. However, from an ontological engineering viewpoint, some ontologies offer systematized knowledge, developed under close cooperation between domain experts and ontology engineers. Such ontologies could be a valuable knowledge base for advanced information systems. Although ontologies in RDF formats using OWL or RDF(S) can be published as linked data, it is not always convenient to use other applications because of the complicated graph structures. Consequently, this paper discusses RDF data models for publishing ontologies as linked data. As a case study, we focus on a disease ontology in which diseases are defined as causal chains.

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Notes

  1. 1.

    When we searched for “ontology” as a keyword on the data catalog, 43 datasets were found at http://datahub.io/group/lodcloud. Also, 402 datasets were found at http://datahub.io/ and 365 of them have “lod” tag. These searches were conducted on August 17th, 2013.

  2. 2.

    http://dbpedia.org/

  3. 3.

    http://mappings.dbpedia.org/server/ontology/

  4. 4.

    http://bioportal.bioontology.org/. The number was checked on August 17th, 2013.

  5. 5.

    http://www.cyc.com/

  6. 6.

    https://wordnet.princeton.edu/

  7. 7.

    http://www.ihtsdo.org/snomed-ct/

  8. 8.

    http://www.opengalen.org/

  9. 9.

    http://www.wikipediaontology.org/query/

  10. 10.

    Note that we used a simplified OWL representation of the disease ontology to show its overview while it does not support full semantics of Hozo. The detailed semantics of Hozo are discussed in [10].

  11. 11.

    Note that property names such as hasCause and hasCoreState represent owl:Restriction on them in Figs. 3 and 4.

  12. 12.

    If probability of the causal relationship is high, hasProbableCause/hasProbableResult properties are used instead. We do not discuss how its probability is decided since it is beyond the scope of this paper.

  13. 13.

    If there are more than two possible causes/results, owl:unionOf is used to list them.

  14. 14.

    Although the disease ontology includes definitions diseases in 13 clinical areas, we published parts of them that were well reviewed by clinicians. The rest of them will be published after reviews.

  15. 15.

    http://semanticweb.cs.vu.nl/lod/wn30/

  16. 16.

    http://www.spatial.redlands.edu/sds/

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Acknowledgement

A part of this research is supported by the Japan Society for the Promotion of Science (JSPS) through its “FIRST Program" and the Ministry of Health, Labour and Welfare, Japan. The authors are deeply grateful to medical doctors (Natsuko Ohtomo, Aki Hayashi, Takayoshi Matsumura, Ryota Sakurai, Satomi Terada, Kayo Waki, et.al.), of The University of Tokyo Hospital for describing disease ontology and providing us with broad clinical knowledge. The authors also would like to thank Hiroko Kou for describing the primary version of disease ontology, Nobutake Kato for implementation the proposed systems and Enago (www.enago.jp) for the English language review.

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Authors and Affiliations

  1. The Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka, 567-0047, Japan

    Kouji Kozaki & Yuki Yamagata

  2. Department of Planning Information and Management, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan

    Takeshi Imai

  3. Department of Medical Informatics Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan

    Kazuhiko Ohe

  4. Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa, 923-1292, Japan

    Riichiro Mizoguchi

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  1. Kouji Kozaki
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  2. Yuki Yamagata
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  3. Takeshi Imai
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  4. Kazuhiko Ohe
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  5. Riichiro Mizoguchi
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Correspondence to Kouji Kozaki .

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Editors and Affiliations

  1. Yonsei University, Seoul, Korea, Republic of (South Korea)

    Wooju Kim

  2. Indiana University, Bloomington, Indiana, USA

    Ying Ding

  3. Seoul National University, Seoul, Korea, Republic of (South Korea)

    Hong-Gee Kim

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Kozaki, K., Yamagata, Y., Imai, T., Ohe, K., Mizoguchi, R. (2014). Publishing a Disease Ontologies as Linked Data. In: Kim, W., Ding, Y., Kim, HG. (eds) Semantic Technology. JIST 2013. Lecture Notes in Computer Science(), vol 8388. Springer, Cham. https://doi.org/10.1007/978-3-319-06826-8_10

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  • DOI: https://doi.org/10.1007/978-3-319-06826-8_10

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