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Automated Quality Evaluation for a More Effective Data Peer Review

Dusterhus, A.; Hense, A.. 2014 Automated Quality Evaluation for a More Effective Data Peer Review. Data Science Journal, 13. 67-78. 10.2481/dsj.14-009

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.
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Programmes:
NOC Programmes > Marine Physics and Ocean Climate
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