Edited by: Dr. Leyla Jael Castro and Dr. Nuria Queralt-Rosinach
Data-driven research follows a cycle involving data as well as other research/digital objects such as publications, tools (e.g. software and workflows) or knowledge transfer (e.g. training materials, tutorials, guidelines) together with metadata enrichment and FAIRification processes. To succesfully follow this cycle, we need research objects management plans supporting the findable, accessible, interoperable and reusable (FAIR) principles, i.e., rather than static documents, we need machine-actionable plans enriched with metadata as well as meaningful links other relevant research objects and their corresponding management plans (including FAIRification). Additional elements should be taken into account to also support Data Spaces/Ecosystems as well as Open Science. This collection welcomes contributions on data and research objects management plans, FAIRification supporting Open Science, and research supporting open and transparent digital research ecosystems.