Speakers
Description
From the perspectives of different data (re-)use cases (from University Library, Research Funding Support, Super Computing Centre and LMU Physics Department), this talk will focus on the many aspects of FAIR data. In practice, data should be handled in accordance to the FAIR (Findable, Accessible, Interoperable, Reusable) principles – but what does this mean in scientific day-to-day work? Starting with the framework provided by research funders and scientific journals, we will explore what makes your data FAIR and how you can also benefit from having your data FAIRified. In this context, the role of data management plans, metadata, data publication and Open Data will show, how inseparable data driven research and FAIR are linked. To wrap it up, helpful tools and infrastructures are shown as well as best practice examples from how large datasets are handled by LMU Munich and LRZ.
