2nd Workshop on Data and research objects management for Linked Open Science
Research data is the mirror of experimental work. Data, together with the software used to produce and analyze it, complements scientific publications and is core input to data- and knowledge-driven research. Most research activities follow the research data cycle, where data is continuously produced , transformed and (re)used, transitioning from one research to another. For this cycle to prosper, we require Research Data and Research Objects Management (RDM and ROM) plans supporting the findable, accessible, interoperable and reusable (FAIR) principles. Despite playing an important role, data on its own is not sufficient to establish Open Science nor Linked Open Science, i.e., Open Science plus Linked Open Data (LOD) principles. LOD principles, aka LOD 5 stars, follow objectives that overlap with FAIR principles and Open Science (e.g., LOD 5 stars include “openness” and the use of “non-proprietary open formats”). In this workshop we will explore what is required for RDM to effectively instantiate Linked Open Science, including effective support for LOD, automation by, e.g.,machine/deep learning approaches, FAIR and Data Spaces/Ecosystems. Furthermore, we are interested in innovations to also support other Research Objects such as software and workflows, in order to get an integrated layer supporting all the edges of Linked Open Science. We welcome contributions on data and research objects management plans, FAIRification supporting Open Science, linking approaches on metadata + publications + data + software, and research supporting open and transparent digital research ecosystems.