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SCIVO: Skills to Career with Interests and Values Ontology

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Knowledge Graphs and Semantic Web (KGSWC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14382))

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Abstract

While getting a doctorate degree, new skills are acquired, opening up multiple traditional and non-traditional avenues of future employment. To help doctoral students explore the available career paths based on their skills, interests and values, we built a findable, accessible, interoperable, and reusable Skills to Career with Interests and Values ontology (SCIVO). It is a compact ontology of seven classes to harmonize the heterogeneous resources available providing information related to career paths. We demonstrate the interoperability and usability of SCIVO through building a knowledge graph using the web scraped publicly available data from the Science Individual Development Plan tool for current doctoral students - myIDP and the National Science Foundation Survey of Earned Doctorates (NSF SED) 2019 data. The generated knowledge graph (named SCIVOKG) consists of one hundred and sixteen classes and one-thousand seven-hundred and forty instances. An evaluation is conducted using application-based competency questions generated by analyzing data collected through surveys and individual interviews with current doctoral students. SCIVO provides an ontological foundation for building a harmonized resource as an aid to doctoral students in exploring the career options based on their skills, interests and values.

Resource Website:

https://tetherless-world.github.io/sciv-ontology/.

Supported by the RPI-IBM AI Research Collaboration, a member of the IBM AI Horizons network.

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Notes

  1. 1.

    https://tetherless-world.github.io/sciv-ontology/.

  2. 2.

    https://github.com/protegeproject/mapping-master/wiki/MappingMasterDSL.

  3. 3.

    A knowledge graph is referred to the graph created by expanding and instantiating SCIVO classes and referred to as SCIVOKG.

  4. 4.

    Resource Website: https://tetherless-world.github.io/sciv-ontology/.

  5. 5.

    Resource Website: https://tetherless-world.github.io/sciv-ontology/.

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Acknowledgement

This work is a part of “Building a Social Machine for Graduate Mobility”. We would like to thank Dean Stanley Dunn, Dean of Graduate Education, who provided expert insights into this issue. We would like to thank the members of the Tetherless World Constellation Lab at Rensselaer Polytechnic Institute who provided insights and expertise that greatly assisted this research. This work was funded in part by the RPI-IBM AI Research Collaboration, a member of the IBM AI Horizons network.

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Authors and Affiliations

  1. Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA

    Neha Keshan & James A. Hendler

Authors
  1. Neha Keshan
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  2. James A. Hendler
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Corresponding author

Correspondence to Neha Keshan .

Editor information

Editors and Affiliations

  1. Autonomous University of Tamaulipas, Ciudad Victoria, Mexico

    Fernando Ortiz-Rodriguez

  2. University of La Rioja, Madrid, Spain

    Boris Villazón-Terrazas

  3. Autonomous University of Tamaulipas, Ciudad Victoria, Mexico

    Sanju Tiwari

  4. University of Zaragoza, Zaragoza, Spain

    Carlos Bobed

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Keshan, N., Hendler, J.A. (2023). SCIVO: Skills to Career with Interests and Values Ontology. In: Ortiz-Rodriguez, F., Villazón-Terrazas, B., Tiwari, S., Bobed, C. (eds) Knowledge Graphs and Semantic Web. KGSWC 2023. Lecture Notes in Computer Science, vol 14382. Springer, Cham. https://doi.org/10.1007/978-3-031-47745-4_19

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  • DOI: https://doi.org/10.1007/978-3-031-47745-4_19

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  • Online ISBN: 978-3-031-47745-4

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