Data Science Journal (Jun 2014)

Automated Quality Evaluation for a More Effective Data Peer Review

  • A Düsterhus,
  • Hense A

DOI
https://doi.org/10.2481/dsj.14-009
Journal volume & issue
Vol. 13
pp. 67 – 78

Abstract

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A peer review scheme comparable to that used in traditional scientific journals is a major element missing in bringing publications of raw data up to standards equivalent to those of traditional publications. This paper introduces a quality evaluation process designed to analyse the technical quality as well as the content of a dataset. This process is based on quality tests, the results of which are evaluated with the help of the knowledge of an expert. As a result, the quality is estimated by a single value only. Further, the paper includes an application and a critical discussion on the potential for success, the possible introduction of the process into data centres, and practical implications of the scheme.

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