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
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Abstract/Summary
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.
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | 10.2481/dsj.14-009 |
ISSN: | 1683-1470 |
Additional Keywords: | Data peer review, Data publication, Quality evaluation, Statistical quality assurance, Meteorological data |
Date made live: | 11 Jun 2014 14:14 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/507423 |
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