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Joint International Semantic Technology Conference

JIST 2017: Semantic Technology pp 268–276Cite as

Semantic Graph Analysis for Federated LOD Surfing in Life Sciences

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10675))

Abstract

Currently, Linked Open Data (LOD) is increasingly used when publishing life science databases. To facilitate flexible use of such databases, we employ a method that uses federated query search along a path of class–class relationships. However, an effective method for federated query search requires analysis of the structure the relationships form for LOD datasets. Therefore, we constructed a graph of class–class relationships among 43 SPARQL endpoints and analyzed the connectivity of the graph. As a result, we found that (1) the sizes of connected components follow a power law; thus we should deal with the classes separately according to the size of connected components, (2) only the largest and second largest connected components have paths among classes from two or more SPARQL endpoints, and the datasets of each of the two connected components share ontologies, and (3) key classes that connect SPARQL endpoints are primarily upper-level concepts in the biological domain.

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Notes

  1. 1.

    http://www4.wiwiss.fu-berlin.de/drugbank/sparql.

  2. 2.

    https://id.nlm.nih.gov/mesh/sparql.

  3. 3.

    https://dba-rdf.biosciencedbc.jp/sparql.

  4. 4.

    http://data.organic-edunet.eu/sparql.

  5. 5.

    http://sparql.wikipathways.org.

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Acknowledgments

This work was supported by JSPS KAKENHI grant numbers 17K00434, 17K00424 and 17H01789, and by the National Bioscience Database Center (NBDC) of the Japan Science and Technology Agency (JST).

Author information

Authors and Affiliations

  1. Database Center for Life Science (DBCLS), Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871, Japan

    Atsuko Yamaguchi & Yasunori Yamamoto

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

    Kouji Kozaki

  3. RIKEN BioResource Center (BRC), 3-1-1, Koyadai, Tsukuba, Ibaraki, 305-0074, Japan

    Hiroshi Masuya & Norio Kobayashi

  4. Advanced Center for Computing and Communication (ACCC), RIKEN, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan

    Hiroshi Masuya & Norio Kobayashi

Authors
  1. Atsuko Yamaguchi
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  2. Kouji Kozaki
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  3. Yasunori Yamamoto
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  4. Hiroshi Masuya
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  5. Norio Kobayashi
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Corresponding author

Correspondence to Atsuko Yamaguchi .

Editor information

Editors and Affiliations

  1. Griffith University, Brisbane, Queensland, Australia

    Zhe Wang

  2. Dresden University of Technology, Dresden, Germany

    Anni-Yasmin Turhan

  3. Griffith University, Brisbane, Queensland, Australia

    Kewen Wang

  4. Tianjin University, Tianjin, China

    Xiaowang Zhang

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Yamaguchi, A., Kozaki, K., Yamamoto, Y., Masuya, H., Kobayashi, N. (2017). Semantic Graph Analysis for Federated LOD Surfing in Life Sciences. In: Wang, Z., Turhan, AY., Wang, K., Zhang, X. (eds) Semantic Technology. JIST 2017. Lecture Notes in Computer Science(), vol 10675. Springer, Cham. https://doi.org/10.1007/978-3-319-70682-5_18

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  • DOI: https://doi.org/10.1007/978-3-319-70682-5_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70681-8

  • Online ISBN: 978-3-319-70682-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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