#PRCN2019: Improving Datasets in Pure

Presented by

Dimitri Unger, Vrije Universiteit, Amsterdam, Netherlands. Reingis Hauck, Leibniz University, Hannover, Germany

About this talk

The status of datasets within research has become more prominent, which is apparent by the increased adaptation of the FAIR principles. It has become clear that data may be one of the most valuable products resulting from research. The need to collect and profile metadata on datasets is growing. This is because it will lead to even better research through sharing and reusing data. Pure can help to facilitate these ambitions, but if improved it can serve them even better. In different user groups Pure managers have looked at the ways Pure can help researchers when it comes to datasets. Our findings could be categorized under the following fields: Interconnectivity, Usability, Administration and Profiling. Through this poster we would like to present the findings on how to improve datasets in Pure.

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