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Automated Quality Evaluation for a More Effective Data Peer Review

Authors:

A Düsterhus ,

National Oceanography Centre, Joseph Proudman Building, 6 Brownlow Street, Liverpool L3 5DA, United Kingdom. Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn, Germany
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Hense A

Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn, Germany
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Abstract

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.
DOI: http://doi.org/10.2481/dsj.14-009
How to Cite: Düsterhus, A. & A, H., (2014). Automated Quality Evaluation for a More Effective Data Peer Review. Data Science Journal. 13, pp.67–78. DOI: http://doi.org/10.2481/dsj.14-009
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Published on 05 Jun 2014.
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