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

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

Jia Zhang, Chris Lee, Petr Votava, Tsengdar J. Lee, Shuai Wang, Venkatesh Sriram, Neeraj Saini, Pujita Rao, Ramakrishna Nemani
Copyright: © 2015 |Volume: 12 |Issue: 3 |Pages: 23
ISSN: 1545-7362|EISSN: 1546-5004|EISBN13: 9781466675735|DOI: 10.4018/IJWSR.2015070102
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MLA

Zhang, Jia, et al. "A Trust-Powered Technique to Facilitate Scientific Tool Discovery and Recommendation." IJWSR vol.12, no.3 2015: pp.25-47. http://doi.org/10.4018/IJWSR.2015070102

APA

Zhang, J., Lee, C., Votava, P., Lee, T. J., Wang, S., Sriram, V., Saini, N., Rao, P., & Nemani, R. (2015). A Trust-Powered Technique to Facilitate Scientific Tool Discovery and Recommendation. International Journal of Web Services Research (IJWSR), 12(3), 25-47. http://doi.org/10.4018/IJWSR.2015070102

Chicago

Zhang, Jia, et al. "A Trust-Powered Technique to Facilitate Scientific Tool Discovery and Recommendation," International Journal of Web Services Research (IJWSR) 12, no.3: 25-47. http://doi.org/10.4018/IJWSR.2015070102

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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.

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