Institut für Pflanzenbau und Bodenkunde
Approved data quality is a prerequisite for the reusability of data. crop-relevant data are characterized by heterogeneity with distinct quality requirements and open issues. This includes, for instance, dependencies of spatial, spectral and temporal resolutions of time series data on modelling results, uncertainties related to data aggregation levels and their scale-specific representativity, the accuracy and completeness of phenotyping and legacy data, and the plausibility of data from long term agricultural field experiments (LTE). In summary, data quality review, curation and documentation are needed; however, community-driven standard criteria are still lacking. Based on existing and representative agrosystem datasets related to FAIRagro Use Cases, relevant data quality metrics with special considerations of data-fitness-for-use aspects will be identified, formalized and transferred to application-specific queries. The work leads to an exemplary data-for-fitness-curation primers and a curation geodata/LTE data checklist for the data stewards. The outcomes support the definition of additional FAIRagro quality metadata descriptors and are incorporated into the FAIRagro inventory and search service.1. Action 1 (Identification of relevant agrosystem data quality aspects) For better transparency, exemplary data use profiles are documented, commented and visualized. In addition, relevant data quality aspects required for typical applications in agrosystems related to LTE and geodata based on Use Caes and community workshops will be identified and documented.2. Action 2 (Data-for-fitness-use formalization): We take an important step from rather generic data quality standards towards an application-specific formalization of the fitness-for-use of data in a multidimensional application-data-matrix framework. A selected set of data-fitness elements in the FAIRness measurement templates as well as a proposal of new metadata elements for data fitness classifications will be developed. For typical data from long-term experiments and for geodata we will construct a visualization and documentation system for the relationships between the quality of the input data and the expected quality of the outcome of an analysis.3. Action 3 (Definition of application-specific queries): As soon as exemplary data quality metrics are published, we will determine typical application-specific queries that will be documented, presented and discussed with the community, and operationalized. The formal technical representation and accompanying samples, e.g., for queries, will be provided, which will facilitate the findability of dataset fit for specific applications. Such queries can then be issued either by data users or through search engine-like interfaces.
German Research Foundation
