| Data Science Journal | |
| Automated Quality Evaluation for a More Effective Data Peer Review | |
| A Hense1  A Düsterhus2  | |
| [1] Meteorological Institute, University of Bonn;National Oceanography Centre | |
| 关键词: Data peer review; Data publication; Quality evaluation; Statistical quality assurance; Meteorological data; | |
| DOI : 10.2481/dsj.14-009 | |
| 学科分类:计算机科学(综合) | |
| 来源: Ubiquity Press Ltd. | |
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【 摘 要 】
References(22)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.
【 授权许可】
Unknown
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| RO201911300035330ZK.pdf | 2372KB |
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