Author: Sonja Herres-Pawlis

Research data management (RDM) is needed to assist experimental advances and data collection in the chemical sciences.

Many funders require RDM because experiments are often paid for by taxpayers and the resulting data should be deposited sustainably for posterity. However, paper notebooks are still common in laboratories and research data is often stored in proprietary and/or dead-end file formats without experimental context. Data must mature beyond a mere supplement to a research paper. Electronic lab notebooks (ELN) and laboratory information management systems (LIMS) allow researchers to manage data better and they simplify research and publication. Thus, an agreement is needed on minimum information standards for data handling to support structured approaches to data reporting. As digitalization becomes part of curricular teaching, future generations of digitally native chemists will embrace RDM and ELN as an organic part of their research. Our call for minimum information standards in chemistry can be found here.

The atomic number is the only chemical feature that is used to derive the TUCAN format. Other than that, the format is solely based on the molecular topology. The serialisation procedure generates a canonical “tuple-style” output which is bidirectional, allowing the TUCAN string to serve as both identifier and descriptor. Use of the Python NetworkX graph library facilitated a compact and easily extensible implementation. Now, an online version (Figure 1) is presented where chemists can have a look and try to convert their molecules into the TUCAN format, either from drawing directly or from a mol-file.

Furthermore, the work on the TUCAN identifier and descriptor has just been published in the Journal of Cheminformatics.

Technical sessions were held in-person and virtually from June 17 to 19 for several of the extension projects for the InChI Standard. Topics covered included organometallics, extended stereochemistry and tautomers.

Notably, the group agreed to maintain metal connectivity in further InChI developments which will solve many problems in the description of molecular inorganic compounds – arguably the most important conclusion of the meeting. If you are interested in the InChI Outreach to receive the latest news and information about the InChI code, please click here.

In the research article in the Journal of Computational Chemistry entitled “Geometrical benchmarking and analysis of redox potentials of copper(I/II) guanidine-quinoline complexes: Comparison of semi-empirical tight-binding and DFT methods and the challenge of describing the entatic state (part III)” Herres-Pawlis & Leonhardt et al. describe copper model complexes for the entatic state theoretically.

They use the semi-empirical tight-binding method GFN2-xTB, the density functional TPSSh and the double-hybrid functional B2PLYP and evaluate the methods on five different complex pairs (Cu(I) and Cu(II) complexes), and compare how well calculated energies can predict the redox potentials. They find that B2PLYP and TPSSh yield better accordance with the experimental structures but that GFN2-xTB performs surprisingly well in the geometry optimisation at a fraction of the computational cost. TPSSh offers a good compromise between computational cost and accuracy of the redox potential for real-life complexes.

The DFT coordinates have been deposited at the RADAR4Chem repository (dataset). RADAR4Chem accepts every kind of chemical data annotated with their metadata.

Sharing of data with the scientific community plays an important role in conducting FAIR and sustainable research. As an example, reporting experimental results (also negative ones) in a systematic, machine-readable way will enable automated data curation and machine learning processes in the near future.

On the smallest scale, experimental data are shared within laboratories, working groups, or institutions. The electronic laboratory notebook Chemotion provides a sharing feature which allows to share data easily with others on various hierarchy levels and furthermore offers the possibility to generate joint databases for almost every desirable need.

In this publication in Chemistry-Methods, we explain the sharing feature of Chemotion and propose a sharing policy as a best practice model to have a consistent and easily applicable guideline for all scientists in a laboratory, working group, or institution. These guidelines may serve as a foundation and recommendation for other scientists who like to use the ELN Chemotion and its sharing feature.

Read more: F. Fink, H. M. Hüppe, N. Jung, A. Hoffmann, S. Herres-Pawlis,Sharing is Caring: Guidelines for Sharing in the Electronic Laboratory Notebook (ELN) Chemotion as applied by a Synthesis-oriented Working Group, Chem. Methods 2022, doi: 10.1002/cmtd.202200026.

From June 21 to 24, the world’s leading trade fair for laboratory technology, analysis, and biotechnology, the Analytica, took place in Munich. At the accompanying Analytica conference researchers, scientists, users, and manufacturers from around the world gave talks to promote the interconnection of science and industry. The programme distributed over three days and several sessions focussed as usual on various interdisciplinary and future-oriented topics, e.g. analytics, diagnostics, measurements or biotechnology.

As one of this year’s highlights, the German Society for Biochemistry and Molecular Biology (GBM), the German Society for Clinical Chemistry and Laboratory Medicine e.V. (DGKL), and the German Chemical Society (GDCh) dedicated a whole conference day to the topic of Research Data Management (RDM). On June 23 three consecutive sessions chaired by the respective societies featured different aspects of RDM. Within GDCh’s final session “Research Data Management III” Fabian Fink from the Herres-Pawlis group at RWTH Aachen University presented NFDI4Chem and the software Chemotion with its electronic laboratory notebook (ELN) and repository. The presentation slides are published on Zenodo, where they are freely accessible and downloadable. The presentation preceded a talk about the BAM Data Store by Dr. Rukeia El-Atman, a short introduction on The Carpentries by chair Dr. Claudia Beleites, and a panel discussion on the necessity and challenges of RDM. This fruitful discussion between the speakers, the chair, and the audience was a successful conclusion to the particular session and the Analytica conference in general.

The sections are bodies of the NFDI e.V. in which members of all NFDI consortia work together on various cross-cutting topics of common interest. This spring the sections elected their spokespersons. We congratulate all newly elected spokespersons, particularly of course the members of our own consortium:

Section (Meta)data, Terminologies, Provenance (Metadata)
Spokespersons: Dr. Oliver Koepler (TIB), Jun. Prof. Dr. Brigitte Mathiak (University of Cologne)

Section Education and Training (EduTrain)
Spokespersons: Prof. Dr. Peter Pelz (University of Darmstadt), Prof. Dr. Sonja Herres-Pawlis (RWTH Aachen University)

Section Common Infrastructures (CI)
Spokespersons: Dr. Michael Diepenbroek (Gesellschaft für Biologische Daten e.V. (GFBio e.V.), Prof. Dr. Sonja Schimmler (Fraunhofer FOKUS)

Section Ethical, Legal & Social Aspects
Spokespersons: Prof. Franziska Boehm (FIZ Karlsruhe), Ulrich Sax (Georg-August-Universität Göttingen)

More information about the sections, their agenda and working groups will be published on the NFDI website soon. If you are interested in joining one of the working groups in the sections please get in touch with the responsible spokespersons.

All sections have contributed to the proposal for “Basic Services for the NFDI” Base4NFDI which was submitted as a joint proposal of all 19 NFDI consortia on April 29. Base4NFDI will develop basic services for the NFDI and is the final outcome of the cross-cutting topics discussion across the consortia since the beginning of NFDI in 2019. As a result, more than a dozen topics emerged where NFDI-wide services seem plausible and/or desirable to enable interoperability, achieve synergies and economies of scale and/or cost-efficient development and operation. [ref: https://www.dfg.de/download/pdf/foerderung/programme/nfdi/absichtserklaerungen_2022/2022_base4_nfdi.pdf]