
In the face of the global shift toward Open Science, policies accelerate cultural change and enable academic institutions, funders, research infrastructures, and publishers to develop their position in the discourse. Policies can reference norms from a wider setting, for example scientific societies or the FAIR Principles. They can also serve as a motivator for researchers to participate in Open Science practices, for example publishing articles Open Access or making code and research data available. However, in order to turn policies into practice, a research-supported infrastructure is necessary. Dedicated repositories facilitate the implementation of these policies, for example by making research output available under open licenses. In this SciDataCon session, we explored how various stakeholders develop research data policies, and particularly the interrelation of policies and research data repositories. Repositories are at the core of data sharing, as they provide the means to store, curate, publish, and preserve research data. Furthermore, they generate, consolidate and maintain metadata, thus supporting the findability, accessibility, interoperability, and reusability of datasets. This topic has led to the creation of various guideline documents and recommendations in recent years, but also to controversial discussions. The session included lightning talks from the perspective of various stakeholders that have developed policies and guidelines for Open Science practices and research data handling, namely research organizations, funding organizations, journals, and research data repositories. These insights were followed by a presentation on the topic of harmonization and standardization of data policies, which is a key motivation for activities in the national and international research data community. The proposed session was organized by members of the DFG-funded re3data COREF project.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
