Collaborative creation and management of rich FAIR metadata: Two case studies from robotics field research

This paper presents lessons learned from the creation and management of FAIR (Findable, Accessible, Interoperable, Reusable) data and metadata in two recent robotics projects, in order to derive principles and building blocks for collaborative (meta)data management in field research. First, an inventory of metadata purposes and topics is presented, distinguishing between executive metadata necessary for data producers, and rich reusable metadata satisfying the FAIR principles. A model of the metadata creation process is developed and compared with the Metadata4Ing ontology. Second, social aspects of FAIR research data management (RDM) are discussed in the project context and beyond. The primary tasks of a FAIR research data manager are analyzed in three domains: data production team, research domain, and FAIR RDM community. Third, some improvements on prominent data lifecycle models are proposed to support the requirements of collaborative RDM, and to foster an iterative improvement of RDM systems.