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Research Conference on Metadata and Semantics Research

MTSR 2016: Metadata and Semantics Research pp 333–344Cite as

DSCrank: A Method for Selection and Ranking of Datasets

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 672))

Abstract

Considerable efforts have been made to build the Web of Data. One of the main challenges has to do with how to identify the most related datasets to connect to. Another challenge is to publish a local dataset into the Web of Data, following the Linked Data principles. The present work is based on the idea that a set of activities should guide the user on the publication of a new dataset into the Web of Data. It presents the specification and implementation of two initial activities, which correspond to the crawling and ranking of a selected set of existing published datasets. The proposed implementation is based on the focused crawling approach, adapting it to address the Linked Data principles. Moreover, the dataset ranking is based on a quick glimpse into the content of the selected datasets. Additionally, the paper presents a case study in the Biomedical area to validate the implemented approach, and it shows promising results with respect to scalability and performance.

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Notes

  1. 1.

    http://www.w3.org/rdf.

  2. 2.

    http://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenData.

  3. 3.

    http://www.obofoundry.org/.

  4. 4.

    https://www.w3.org/TR/sparql11-overview/.

  5. 5.

    http://bioknowlogy.biowebdb.org.

  6. 6.

    http://ckan.org/about/.

  7. 7.

    http://download.bio2rdf.org/release/3/release.html.

  8. 8.

    http://rdf4j.org/about.docbook?view.

  9. 9.

    http://wordnet.princeton.edu/wordnet/download.

  10. 10.

    http://info.ils.indiana.edu/~stevecox/unix/s603/man/grep.1.pdf.

  11. 11.

    http://bioknowlogy.biowebdb.org/metaresistomedb/sparql-vt.php.

  12. 12.

    http://ypublish.info/pdf-validation-table.pdf.

  13. 13.

    http://linkeddatacatalog.dws.informatik.uni-mannheim.de/dataset?q=lifescience&sort=score+desc,+metadata_modified+desc.

  14. 14.

    Ratio between relevant datasets retrieved and the number of top ranked datasets.

  15. 15.

    http://download.openbiocloud.org/release/3/release.html.

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Acknowledgements

This work was partially funded by CAPES scholarship, CNPq (proc. 307647/2012-9) and FAPERJ (Proc.E-26/111.147/2011).

Author information

Authors and Affiliations

  1. Military Institute of Engineering, Rio de Janeiro, Brazil

    Yasmmin Cortes Martins & Maria Cláudia Cavalcanti

  2. IOC/FIOCRUZ, Rio de Janeiro, Brazil

    Fábio Faria da Mota

  3. National Laboratory of Scientific Computing, Petrópolis, Brazil

    Yasmmin Cortes Martins

Authors
  1. Yasmmin Cortes Martins
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  2. Fábio Faria da Mota
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  3. Maria Cláudia Cavalcanti
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Corresponding author

Correspondence to Yasmmin Cortes Martins .

Editor information

Editors and Affiliations

  1. Alexander Technological Educational Institute of Thessaloniki, Thessaloniki, Greece

    Emmanouel Garoufallou

  2. Alexander Technological Educational Inst , Rome, Italy

    Imma Subirats Coll

  3. Sapienza University of Rome , Rome, Italy

    Armando Stellato

  4. Drexel University, Philadelphia, Pennsylvania, USA

    Jane Greenberg

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Martins, Y.C., da Mota, F.F., Cavalcanti, M.C. (2016). DSCrank: A Method for Selection and Ranking of Datasets. In: Garoufallou, E., Subirats Coll, I., Stellato, A., Greenberg, J. (eds) Metadata and Semantics Research. MTSR 2016. Communications in Computer and Information Science, vol 672. Springer, Cham. https://doi.org/10.1007/978-3-319-49157-8_29

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  • DOI: https://doi.org/10.1007/978-3-319-49157-8_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49156-1

  • Online ISBN: 978-3-319-49157-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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