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A Trust-Powered Technique to Facilitate Scientific Tool Discovery and Recommendation

Author

Listed:
  • Jia Zhang

    (Carnegie Mellon University, Silicon Valley, CA, USA)

  • Chris Lee

    (Carnegie Mellon University, Silicon Valley, CA, USA)

  • Petr Votava

    (NASA Ames Research Center, Silicon Valley, USA & Science Mission Directorate, NASA Headquarters, Washington, D.C., USA)

  • Tsengdar J. Lee

    (Science Mission Directorate, NASA Headquarters, Washington, D.C., USA)

  • Shuai Wang

    (Carnegie Mellon University, Silicon Valley, CA, USA)

  • Venkatesh Sriram

    (Carnegie Mellon University, Silicon Valley, CA, USA)

  • Neeraj Saini

    (Carnegie Mellon University, Silicon Valley, CA, USA)

  • Pujita Rao

    (Carnegie Mellon University, Silicon Valley, CA, USA)

  • Ramakrishna Nemani

    (NASA Ames Research Center, Silicon Valley, CA, USA)

Abstract

While the open science community engenders many similar scientific tools as services, how to differentiate them and help scientists select and reuse existing software services developed by peers remains a challenge. Most of the existing service discovery approaches focus on finding candidate services based on functional and non-functional requirements as well as historical usage analysis. Complementary to the existing methods, this paper proposes to leverage human trust to facilitate software service selection and recommendation. A trust model is presented that leverages the implicit human factor to help quantify the trustworthiness of candidate services. A hierarchical Knowledge-Social-Trust (KST) network model is established to extract hidden knowledge from various publication repositories (e.g., DBLP) and social networks (e.g., Twitter and DBLP). As a proof of concept, a prototyping service has been developed to help scientists evaluate and visualize trust of services. The performance factor is studied and experience is reported.

Suggested Citation

  • Jia Zhang & Chris Lee & Petr Votava & Tsengdar J. Lee & Shuai Wang & Venkatesh Sriram & Neeraj Saini & Pujita Rao & Ramakrishna Nemani, 2015. "A Trust-Powered Technique to Facilitate Scientific Tool Discovery and Recommendation," International Journal of Web Services Research (IJWSR), IGI Global, vol. 12(3), pages 25-47, July.
    • Handle: RePEc:igg:jwsr00:v:12:y:2015:i:3:p:25-47
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