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

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.


Christian Backe, Veit Briken, Atefeh Gooran Orimi, Rayen Hamlaoui, Malte Wirkus, Bilal Wehbe, Frank Kirchner


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.


There are no comments or no comments have been made public for this article.


Download Preprint

  • Published: 2024-06-10
  • Last Updated: 2024-05-27
  • License: Creative Commons Attribution 4.0
  • Subjects: Data Infrastructure
  • Keywords: Research Data Management, RDM, Metadata, Field Data, FAIR, Robotics
All Preprints