Data Stewardship in the Life Sciences

Open data and integrative data sharing are fundamental factors in order to address the challenges of modern data-intensive science. There is a clear need to develop and maintain community-focussed, semantically-aware data stewardship and management platforms, such as COPO, that are able to cope with the description and sharing of potentially huge datasets arising from the life sciences. Once made available, it is not sufficient to assume that researchers around the globe have requisite skills and resources to analyse these data. Therefore, we need to provide large-scale data analysis environments that are fit for purpose, incorporating state-of-the-art interfaces and programmatic layers to meet broad end-user requirements, such as CyVerse and Galaxy. Finally, this can only happen when there are community-led efforts into implementing solutions for data standardisation, best practice, and FAIR data policy. We are now only just starting to take advantage of groundbreaking opportunities to make integrated data a reality, and thus enabling scientists to store, manage, and share their data as a first-class citizen of the scientific process.