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Sharing research data is a practice that is increasingly encouraged by funders, institutions, and research communities. Policies, tools and training programmes are being developed to assist researchers and data providers to make data available in a way that optimizes data findability, accessibility, interoperability and reusability (i.e. according to the FAIR principles). One of the promises driving both data sharing and policy development is that shared data can and will be discovered and reused; but are users (researchers, librarians, students) discovering this data? And if they are finding them, (how) are they reusing them? In this webinar, organised by LIBER’s Research Data Management Working Group, Kathleen Gregory presented an overview of recent research investigating how researchers and librarians engage in practices of finding, understanding and reusing research data. She provided tips for finding research data and an opportunity for attendees to consider what this research means for developing services at their own organizations.
research data management, reuse, FAIR
research data management, reuse, FAIR
| 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 |
| views | 47 | |
| downloads | 39 |

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Downloads provided by UsageCounts