Automated Research Data Management

Automated Research Data Management

Author: ChemViews Magazine

Many scientists are asking themselves how to effectively organize research data. In the light of increasingly extensive, complex, and heterogeneous data from experiments or simulations, the question gets more urgent. According to good scientific practice, data should be stored for ten years. However, it is unclear in which data formats and where data can be stored in the long term. Publishing data as part of articles or supplements, only to a certain extent meets the requirements and chances of data re-use. The availability of machine-readable data and metadata for emerging research fields in the context of big data and AI algorithms is becoming increasingly important.

In their Editorial in Angewandte Chemie, Sonja Herres-Pawlis, RWTH-Aachen University, Germany, and colleagues introduce the consortium NFDI4Chem. It aims to develop a research data infrastructure for chemistry in a science-driven manner and in line with the needs of researchers. NFDI4Chem consists of data producers and users from German university and non-university research institutions, chemical infrastructure facilities, data centers, and learned societies such as the German Chemical Society (GDCh), the Bunsen Society (DBG), and the German Pharmaceutical Society (DPG). Internationally, NFDI4Chem collaborates with the DIGChem project, a joint initiative of IUPAC, the Research Data Alliance (RDA), Chemistry Research Data Interest Group (CRDIG), and the GO FAIR Chemistry Implementation Network (ChIN), to discuss open data and metadata formats.

The authors ask researchers from Germany and elsewhere to support them in their work by taking a survey before September 15, 2019: And who wants to participate in the chemistry consortium, should write to [email protected].


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