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RVO - The Research Variable Ontology

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The Semantic Web (ESWC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11503))

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Abstract

Enterprises today are presented with a plethora of data, tools and analytics techniques, but lack systems which help analysts to navigate these resources and identify best fitting solutions for their analytics problems. To support enterprise-level data analytics research, this paper presents Research Variable Ontology (RVO), an ontology designed to catalogue and explore essential data analytics design elements such as variables, analytics models and available data sources. RVO is specialised to support researchers with exploratory and predictive analytics problems, popularly practiced in economics and social science domains. We present the RVO design process, its schema, how it links and extends existing ontologies to provide a holistic view of analytics related knowledge and how data analysts at the enterprise level can use it. Capabilities of RVO are illustrated through a case study on House Price Prediction.

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Notes

  1. 1.

    https://wiki.dbpedia.org.

  2. 2.

    http://www.w3.org/TR/vocab-data-cube/.

  3. 3.

    http://purl.org/spar/fabio.

  4. 4.

    http://www.ontodm.com/doku.php?id=ontodt.

  5. 5.

    http://xmlns.com/foaf/spec/.

  6. 6.

    https://www.force11.org/group/fairgroup/fairprinciples.

  7. 7.

    http://dbpedia.org/resource/Gdp.

  8. 8.

    http://adage2.cse.unsw.edu.au/rvo/sparqlEnd.html.

  9. 9.

    https://www.force11.org/group/fairgroup/fairprinciples.

  10. 10.

    http://w3id.org/rv-ontology.

  11. 11.

    https://opensource.org/licenses/MIT.

  12. 12.

    http://w3id.org/rv-ontology/info.

  13. 13.

    https://github.com/madhushib/RVO.

  14. 14.

    http://bioportal.bioontology.org/ontologies/RVO/.

  15. 15.

    http://adage2.cse.unsw.edu.au/rvo/sparqlEnd.html.

  16. 16.

    http://adage2.cse.unsw.edu.au:3000/model-builder.

References

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Acknowledgment

We are grateful to Capsifi, especially Dr. Terry Roach, for sponsoring the research which led to this paper and Gilles Sainte-Marie for developing RVO web page.

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Authors and Affiliations

  1. University of New South Wales, Sydney, Australia

    Madhushi Bandara, Ali Behnaz & Fethi A. Rabhi

Authors
  1. Madhushi Bandara
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  2. Ali Behnaz
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  3. Fethi A. Rabhi
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Corresponding author

Correspondence to Madhushi Bandara .

Editor information

Editors and Affiliations

  1. Wright State University, Dayton, OH, USA

    Pascal Hitzler

  2. KMi, The Open University, Milton Keynes, UK

    Miriam Fernández

  3. University of California, Santa Barbara, CA, USA

    Krzysztof Janowicz

  4. Maastricht University, Maastricht, The Netherlands

    Amrapali Zaveri

  5. Heriot-Watt University, Edinburgh, UK

    Alasdair J.G. Gray

  6. IBM Research, Dublin, Ireland

    Vanessa Lopez

  7. The Australian National University, Canberra, ACT, Australia

    Armin Haller

  8. Jönköping University, Jönköping, Sweden

    Karl Hammar

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Bandara, M., Behnaz, A., Rabhi, F.A. (2019). RVO - The Research Variable Ontology. In: Hitzler, P., et al. The Semantic Web. ESWC 2019. Lecture Notes in Computer Science(), vol 11503. Springer, Cham. https://doi.org/10.1007/978-3-030-21348-0_27

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  • DOI: https://doi.org/10.1007/978-3-030-21348-0_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-21347-3

  • Online ISBN: 978-3-030-21348-0

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