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National Coordination Point Research Data Management: RDM Advice and Tips

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National Coordination Point Research Data Management (LCRDM) is a national network of experts in the field of research data management (RDM). This website includes topics on RDM, data management support, digital competence centres, data infrastructure, guidelines, etc.

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Guidelines for the archiving of academic research for faculties of Behavioural and Social Sciences in the Netherlands

These guidelines for the archiving of academic research set out the preconditions for the archiving of data, materials and information that form the basis for publications – in other words, descriptions of data, materials and information that are needed in order to replicate research results, as well as their storage. These guidelines relate to the data, materials and information with respect to publications that appear in their definitive form as of 1 June 2018. The guidelines are based on the principle of retroactive accountability, i.e. reporting after a publication has appeared. The principle behind these guidelines is that each researcher is responsible for archiving data, materials and information, and the publications based on them, in a responsible and transparent way. In situations where this document does not provide clear-cut rules, researchers are expected to act in the spirit of these guidelines rather than observing them to the letter

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Online Data Horror Escape Room

It is an online escape room game that engages researchers with the principles of research data management (RDM). The game is a collaboration between Vrije Universiteit Amsterdam (Lena Karvovskaya and Elisa Rodenburg), Leiden University Libraries (Joanne Yeomans), and Eindhoven University of Technology (Anne Aarts and Bart Aben).The room we created consists of six tasks related to the following data management topics: FAIR data, personal data, data archiving, data transfer, persistent identifiers, and metadata.

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Research Data Management: more than just storage

Overview of possible costs per activity within each phase of the research process. The format has to be useful not only for researchers, data specialists, but also for funding applicants and funding bodies. An early start for certain activities within the data life cycle (like for instance metadata specification) will lower the costs for data management in the run of the life cycle. A good data management plan before gathering the research data also helps to prevent extra efforts and costs later on in the research cycle.

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