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The Question of Data Integrity in Article-Level Metrics

Author

Listed:
  • Gregg Gordon
  • Jennifer Lin
  • Richard Cave
  • Ralph Dandrea

Abstract

Interest in and use of article-level metrics (ALMs) has grown rapidly amongst the research community, by researchers, publishers, funders, and research institutions. As this happens, it is critical to ensure secure and reliable data that is trustworthy and can be used by all. Two case studies are presented, which illustrate different approaches to establishing ALM data integrity.Article-level metric (ALM) data need to be secure and reliable if they are to be trusted and used by all. This Perspective explores the different approaches taken by two organizations to establish ALM data integrity.

Suggested Citation

  • Gregg Gordon & Jennifer Lin & Richard Cave & Ralph Dandrea, 2015. "The Question of Data Integrity in Article-Level Metrics," PLOS Biology, Public Library of Science, vol. 13(8), pages 1-9, August.
    • Handle: RePEc:plo:pbio00:1002161
    DOI: 10.1371/journal.pbio.1002161
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    References listed on IDEAS

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    1. Adam Dinsmore & Liz Allen & Kevin Dolby, 2014. "Alternative Perspectives on Impact: The Potential of ALMs and Altmetrics to Inform Funders about Research Impact," PLOS Biology, Public Library of Science, vol. 12(11), pages 1-4, November.
    2. Madian Khabsa & C Lee Giles, 2014. "The Number of Scholarly Documents on the Public Web," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-6, May.
    3. Adriano B L Tort & Zé H Targino & Olavo B Amaral, 2012. "Rising Publication Delays Inflate Journal Impact Factors," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-6, December.
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