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Modern research requires special tooling, software and processes that allow researchers to link, transform, visualise and interpret the data. Lack of proper data management practices can lead in extreme cases to irreversible loss of data. As a consequence, reproducibility of scientific experiments can be questioned. This in turn reduces trust in scientific findings and undermines reputation of researchers and their institutions. For this reason, excellent data management skills are nowadays an essential asset to successful researchers. This talk will introduce participants to Data Management Plans that help to plan how data is handled during experiments so that no data is lost, can easily be found, correctly interpreted using provided metadata, and properly licensed. Participants will learn about practical aspects of data management. They will also get familiar with research funder requirements for Data Management Plans that are becoming an obligatory project deliverable around the world. Topics covered: • Why good data management is important? • What are the Data Management Plans? • How to create a Data Management Plan? • What are the best data management practices? • How to make research data FAIR? • What are the funder requirements for Data Management Plans? • What does the future look like concerning data management?
| 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 |
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