Automated quality evaluation for a more effective data peer review

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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 discussionon the potential for success, the possible introduction of the process into data centres, and practical implications of the scheme.

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APA

Düsterhus, A., & Hense, A. (2014). Automated quality evaluation for a more effective data peer review. Data Science Journal, 13, 67–78. https://doi.org/10.2481/dsj.14-009

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