This course discusses the concepts and services that mathematics students often only learn about during thesis writing or by word of mouth. When introducing research data management topics, we focus on how to do maths efficiently and sustainably. In particular:
- Do you know how to look for mathematical results, for formulae, for information about algorithms? How do you find out what is the state of the art of a field? How can you describe a mathematical object so that others know what it is? How can you make sure you sensibly compare your new results to the best ones out there? How can you make your own theoretical and computational results visible and usable for others?
- How do you properly document all the steps in a research process, from a question you are interested in to finding answers to that question up until sharing your results with your peers? Why should you? What has this got to do with applying for funding?
- Have you ever wondered what arXiv is or how the publishing business works? What is (technical) peer review? How are different types of maths, like papers or computations, handled in such an evaluation process? Where and how should you store all the analogue and digital files you handle when doing maths? What are good, sustainable solutions? What is good scientific practice?
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Best practices in mathematics: small trees (MaRDI)
One example of FAIR mathematics is the project small phylogenetic trees: an early 2000’s mathematical library transformed into a modern website, a software package, and a best practice report.
The Health Study Hub: From Data Silos to Knowledge Infrastructure (NFDI4Health)
The Health Study Hub by NFDI4Health brings together studies, instruments, and documents in one central platform, making health research data systematically discoverable and usable. By providing standardized, FAIR-compliant data, it enhances connectivity, reduces duplication, and accelerates research.
From archive to modern research: How animal observations from 1845 provide new insights into biodiversity change (NFDI4Biodiversity)
From Archive to Data Source for Biodiversity Research
Historical wildlife observations from 1845 have been digitized, standardized, and published as FAIR data. This transforms previously hidden archival records into a valuable resource for modern biodiversity research and conservation.
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