Workshop on Data and Research Objects Management for Linked Open Science (2. : 2021 : Online)

Research data is core to data-driven research as it complements scientific publications and expose results from experimental work. Most research activities follow the research data cycle, where data is continuously used, modified and produced, transitioning from one research group to another. For this cycle to prosper, we require Research Data Management plans supporting the findable, accessible, interoperable and reusable (FAIR) principles. Despite playing an important role, data on its own is not enough to fully address challenges posed by the research cycle. To get the full picture, in addition to data, we also need other digital objects playing a role in research, e.g., software and workflows. Further elements need to be taken into account to move towards Open Science, with some additional considerations coming from the Semantic Web to realize Linked Open Science, i.e., Open Science plus Linked Open Data (LOD) principles. In this workshop, we will explore what is required for Research Management Plans addressing data and other research objects to effectively instantiate Linked Open Science, including effective support for LOD, automation by, e.g., machine/deep learning approaches, and innovations to include supporting data elements such as the software used to produce/consume it or the tutorials showcasing usage and fostering further developments.