Providing FAIR sensor data models using semantic web technologies and ontologies

The extended usage time of measurement data due to current trends and regulations demands richly described and FAIR measurement data to ensure (re-) usability by third parties, after long periods, and for different applications. Semantic web technologies and ontologies are key for providing FAIR data, but they significantly increase modelling complexity and effort and lack domain-specific standards. We acknowledge the latter by proposing a semantic data metamodel for measurement data based on domain-agnostic ontologies. To compensate for the increasing complexity, we introduce a mapping to a simple data meta-structure, which can be used to define a measuring system-specific structure and automatically generate the complete semantic measuring system-specific model. Based on these structures and models, we implemented three virtual measuring systems. A FAIRness assessment of the data acquired shows a promising result for the FAIRness of the data but also revealed further possibilities for improving the proposed models and methods.