Challenges in the Evaluation of Observational Data Trustworthiness From a Data Producers Viewpoint (FAIR+)

Recent discussions in many scientific disciplines stress the necessity of “FAIR” data. FAIR data, however, does not necessarily include information on data trustworthiness, where trustworthiness comprises reliability, validity and provenience/provenance. This opens up risk misinterpreting even though all criteria are fulfilled. Especially applications such as secondary processing, blending, joint interpretation or visualization efforts affected. paper intends to start a discussion community about how evaluate, describe, implement standardized evaluation approach its metadata description following principles. It discusses exemplarily different assessment tools regarding soil moisture measurements, processing elaborates which additional (metadata) is required increase for usage. Taking into account perspectives collectors, providers users, authors identify three aspects that promote efficient sharing: 1) measurement 2) 3) integration visualization. The should be seen basis scientifically correct use We do have intention replace existing procedures claim completeness reliable approaches described. Our discuss several important assess based life cycle an example .