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Towards a Scientific Impact Measuring Framework for Large Computing Facilities - a Case Study on XSEDE

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Published:13 July 2014Publication History

ABSTRACT

We present a framework that (a) integrates publication and citation data retrieval, (b) allows scientific impact metrics generation at different aggregation levels, and (c) provides correlation analysis of impact metrics based on publication and citation data with resource allocation for a computing facility. Furthermore, we use this framework to conduct a scientific impact metrics evaluation of XSEDE. We carry out an extensive statistical analysis correlating XSEDE allocation size to the impact metrics aggregated by project and field of science. This analysis not only helps to provide an indication of XSEDE's scientific impact, but also provides insight regarding maximizing the return on investment in terms of allocation by taking into account the field of science or project based impact metrics. The findings from this analysis can be utilized by the XSEDE resource allocation committee to help assess and identify projects with higher scientific impact. It can also help provide metrics regarding the return on investment for XSEDE resources, or other institutional or campus resources for which an analysis of impact based on publications is important.

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      • Published in

        cover image ACM Other conferences
        XSEDE '14: Proceedings of the 2014 Annual Conference on Extreme Science and Engineering Discovery Environment
        July 2014
        445 pages
        ISBN:9781450328937
        DOI:10.1145/2616498
        • General Chair:
        • Scott Lathrop,
        • Program Chair:
        • Jay Alameda

        Copyright © 2014 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 13 July 2014

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        • research-article
        • Research
        • Refereed limited

        Acceptance Rates

        XSEDE '14 Paper Acceptance Rate80of120submissions,67%Overall Acceptance Rate129of190submissions,68%

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