Overview of the Task Areas (TA):
- TA1 – Management: Christoph Steinbeck (Friedrich Schiller University Jena)
- TA2 – Smart Lab: Nicole Jung (Karlsruhe Institute for Technology)
- TA3 – Repository: Felix Bach (Karlsruhe Institute for Technology) & Matthias Razum (FIZ Karlsruhe – Leibniz Institute for Information Infrastructure)
- TA4 – Metadata, Data Standards and Publication Standards: Steffen Neumann (Leibniz Institute for Plant Biochemistry) & Christoph Steinbeck (Friedrich Schiller University Jena)
- TA5 – Community Involvement and Training: Sonja Herres-Pawlis (RWTH Aachen University) & Johannes Liermann (Johannes Gutenberg University Mainz)
- TA6 – Synergies: Oliver Koepler (Leibniz Information Center for Science and Technology TIB Hannover)
I am Steffen Neumann – head of the Research Group Bioinformatics and Scientific Data at the Leibniz Institute of Plant Biochemistry in Halle (Saale). I have prior experience in the area of statistical mass spectrometry data analysis and metabolite identification. In this context, I continuously advocate open data and open standards, leading to community-wide e-infrastructures, and exploiting these for functional annotation through computational metabolomics analyses. I am a member of the scientific advisory board of the French metabolomics infrastructure MetaboHUB, and associate editor for BMC Bioinformatics, MDPI Metabolites, and Nature Scientific Data.
Here in NFDI4Chem, I am co-lead with Chris Steinbeck in task area 4 on Metadata, Data Standards and Publication Standards. This is a truly vast and long term undertaking, and previous experience has shown that continuous persistence and perseverance are required to ensure progress.
I particularly enjoy coordinating the Lead-by-example efforts. Here, we work with the community (you!) to collect research data associated with recent or even upcoming manuscripts to gather, organise, and publish your data sets for and with you. Upcoming manuscripts will then have the benefit of being able to include a “Data availability statement” which points to citable data sets in a suitable resource, such as the Chemotion Repository or RADAR, depending on data types and content.