Table 1
Examples of data quality criteria mentioned in the literature.
| QUALITY CRITERIA | DESCRIPTIONS | SOURCE (EXAMPLE) |
|---|---|---|
| Accessibility | Restrictions to accessing data are kept at a minimum. | Wang & Strong 1996 |
| Accuracy | Data truly and unambiguously represent the phenomena they describe. | Cai & Zhu 2015 |
| Appropriate and correct use of methods | Research methods are appropriately and correctly applied for data collection and processing. | RfII 2020 |
| Appropriateness of metadata/data documentation | Metadata and data documentation appropriately describe data. | Wilkinson et al. 2016 |
| Completeness | All necessary components are present in the data. | CASRAI2022b |
| Consistency | Properties of data are homogeneous and constant. | Batini & Scannapieco 2016 |
| Coverage | Data have the necessary temporal or spatial coverage. | Peng et al. 2022 |
| Open data format | Data are available in an open, nonproprietary format. | OKF n.d. |
| Open data licence | Data are assigned an open licence. | OKF n.d. |
| Reuse potential | The dataset is of value for future analysis by others. | Palmer, Weber & Cragin 2011 |
Figure 1
Types of all repositories indexed in re3data (A; NA: 30) and repositories included in the analysis (B; NA: 6).
Figure 2
Question 05: Are formal criteria applied to data before publication? (A); Question 10: Are data reviewed beyond the application of formal criteria? (B).
Figure 3
Types of data quality assessment performed at responding repositories.
Figure 4
Question 06: Who is responsible for the assessment and curation according to the following formal criteria? (multiple choice).
Figure 5
Question 11: How relevant are the following quality criteria for data review at your repository? (multiple choice).
Figure 6
Question 19: What (estimated) ratio of datasets were rejected by your repository in the last two years?
Figure 7
Publication of results of data quality assurance processes at responding repositories.