20.500.12556/DiRROS-27732 A FAIR perspective on data quality frameworks Despite considerable effort and analysis over the last two to three decades, no integrated scenario yet exists for data quality frameworks. Currently, the choice is between several frameworks dependent upon the type and use of data. While the frameworks are appropriate to their specific purposes, they are generally prescriptive of the quality dimensions they prescribe. We reappraise the basis for measuring data quality by laying out a concept for a framework that addresses data quality from the foundational basis of the FAIR data guiding principles. We advocate for a federated data contextualisation framework able to handle the FAIR-related quality dimensions in the general data contextualisation descriptions and the remaining intrinsic data quality dimensions in associated dedicated context spaces without being overly prescriptive. A framework designed along these lines provides several advantages, not least of which is its ability to encapsulate most other data quality frameworks. Moreover, by contextualising data according to the FAIR data principles, many subjective quality measures are managed automatically and can even be quantified to a degree, whereas objective intrinsic quality measures can be handled to any level of granularity for any data type. This serves to avoid blurring quality dimensions between the data and the data application perspectives as well as to support data quality provenance by providing traceability over a chain of data processing operations. We show by example how some of these concepts can be implemented at a practical level. data quality frameworks FAIR data principles data contextualisation metadata quality provenance data pathway knowledge management federated data true false true Angleški jezik Ni določen Neznano 2026-02-23 14:46:02 2026-02-23 14:46:03 2026-02-24 04:02:02 0000-00-00 00:00:00 2025 0 0 E-članek; Nasl. z nasl. zaslona; Opis vira z dne 25. 8. 2025; str. 1-22 issue 9, [article no.]136 Vol. 10 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.6:001 2306-5729 10.3390/data10090136 246454787 RAZ_Nicholson_Nicholas_2025.pdf RAZ_Nicholson_Nicholas_2025.pdf 1 C3E69D2AD526F0F7DEDBDABB4C31638C 53405840d0f20d3a15b64dd6bf0d650e6761b114e9fc4a3f3ea5e45eff92a0d7 2c3a07cd-10be-11f1-9cb0-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=40742 https://doi.org/10.3390/data10090136 0 384978e6-10be-11f1-9cb0-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=40743 Univerzitetni klinični center Ljubljana 0 0 0