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The IPBES data management tutorials are short videos to help experts implement the IPBES data management Policy. They cover topics ranging from data management policy, reports, active research data, tools, and examples. The Data management of active research data chapter provides an introduction for IPBES experts on how to manage data while actively being used, analyzed, and produced to fulfill the criteria of the IPBES data management policy. This session, Examples of active data management, gives concrete best-practice examples of how the recommendations could be integrated into the daily work of researchers
{"references": ["IPBES (2020): IPBES Data Management Policy ver. 1.0. Task Force on Knowledge and Data, Krug, R.M., Omare, B., and Niamir, A. (eds.) IPBES secretariat, Bonn, Germany. DOI: 10.5281/zenodo.3551079"]}
These tutorials were created in collaboration between the IPBES task force on knowledge and data and the IPBES task force on capacity building. For inquires please contact tsu.data@ipbes.net
IPBES, data management policy
IPBES, data management policy
| 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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