Modern life sciences studies depend on collecting, managing and analysing comprehensive datasets in what has become data-intensive research.

Life science research is also characterised by having relatively small groups of researchers. This combination of data-intensive research performed by a few people has led to an increasing bottleneck in Research Data Management (RDM).

Parallel to this, initiatives like FAIR and Open Science have made an urgent call to openly publish research data, which has put additional pressure on improving the quality of RDM.

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In First-line Research Data Management for Life Sciences: a Case Study (Open Access), the authors reflect on the lessons learnt by DataHub Maastricht.