Johannes C. Liermann

Chemical research data may be handled analogously or digitally in its life cycle, posing digitalisation challenges. The 2nd NFDI4Chem survey (>800 voices) gives updates on the community perspective which is evaluated in comparison to earlier surveys.

The first funding period of NFDI4Chem established a robust foundation for research data management (RDM) in chemistry by promoting FAIR data principles and creating a cohesive infrastructure to capture well-annotated data early in the lab through electronic lab notebooks (ELNs) and making this data available in public repositories. Key achievements include standardised data formats and metadata, a federated repository environment, and improved data visibility and accessibility. Training programs and outreach have significantly increased awareness and adoption of best RDM practices. In the second funding period, the consortium aims to advance these achievements by consolidating this infrastructure, developing a model for its sustainable maintenance and operation, and fostering cultural change for its widespread adoption. Goals include ensuring seamless data workflows from laboratories to open repositories, enhancing interoperability, and supporting innovative research through AI-ready data. The work plan is organised into six task areas (TAs). TA1 (Management) provides leadership and supports all other TAs in achieving their objectives. TA2 (Smart Lab) aims to develop a fully digital research environment, including an ELN as a modular platform. This environment will support data collection, management, storage, analysis, and sharing. Integrating devices and external resources will enable seamless data transfer to repositories. TA3 (Repositories) will consolidate the repository ecosystem. The goal is to integrate repositories into a federated system for better accessibility and interoperability, ensuring long-term data availability and sustainability. TA4 (Metadata, Data Standards, and Publication Standards) focuses on developing and promoting new data and metadata standards in an international community process. This includes applying ontologies to create a semantic foundation for linking research data, making it machine-readable and enabling knowledge graphs. TA5 (Community and Training) is dedicated to fostering a cultural shift towards digital chemistry through continuous engagement, collecting requirements, and providing extensive training and support through workshops and open education resources. It will promote FAIR-compliant machine learning applications, embedding RDM into academic curricula to ensure future scientists are well-versed in these practices. TA6 (Synergies and Cross-Cutting Topics) aims to enhance collaboration across NFDI consortia and beyond. This includes developing ontologies, terminology services, the search service, and other cross-cutting solutions, integrating these developments into existing infrastructure, enabling interdisciplinary data harmonisation and fostering machine learning applications.

The progress of the DFG-funded NFDI4Chem consortium (NFDI 4/1 - project number 441958208) in data management in chemistry is outlined in our latest report, highlighting the steps we have taken to integrate a data-centric approach within the chemistry community. This interim report offers a comprehensive overview of our data management activities, covering the reporting period from October 2020 to August 2023. The shift to digital tools in research documentation is driven by our work with Electronic Laboratory Notebooks (ELNs), such as Chemotion ELN, offering systematic data storage for easy retrieval and sharing. Additionally, we focus on developing repositories, such as Chemotion repository and RADAR4Chem, which fulfil the needs for the storage of chemical data. The NFDI4Chem Search Service ensures easy data access from our repositories. Our efforts extend to community engagement through conference visits and online presence, aimed at creating awareness for (digital) research data management and connecting to chemistry students and researchers. Our training programs have reached over 600 participants to date. Initiatives like the FAIR4Chem award and the Chemistry Data Days promote cultural change towards FAIR data. Our Editors4Chem initiative collaborates with publishers for standardised data management and the Ontologies4Chem workshops organised by our consortium promote the ontology development in the field. Apart from the consortium's engagement for chemists, NFDI4Chem members played key roles in the development of the NFDI as a whole. Being actively involved in the sections and task forces, NFDI4Chem promotes collaborative solutions across NFDI consortia.

NMRium is the first web-based software that allows displaying, processing, interpretation, and teaching of 1D and 2D NMR data in a user-friendly interface. It can import the most common data formats (e.g., JCAMP-DX, Bruker, Varian, and Jeol). While the scope for the use of NMRium encompasses a variety of applications such as being a component in data repositories or electronic lab notebooks (ELN), performing structure elucidation or preparing raw spectral data for publication, it also excels in enhancing teaching of NMR interpretation. In this paper, we present some current possibilities of this new tool. Several series of exercises are already provided on https://www.nmrium.org/teaching.

The Chemistry consortium NFDI4Chem aims to digitalise key steps in chemical research, supporting scientists in managing research data throughout its life cycle. The SmartLab, embedded in a federation of services, integrates various tools such as electronic lab notebooks, data repositories, and search services, to create a smart lab environment for structured data gathering. Utilizing terminology services and adhering to data format standards, NFDI4Chem promotes secure and FAIR data sharing, fostering collaboration and expediting scientific discoveries. This development is supported by community building measures, workshops, and training initiatives, along with collaboration on international minimum information standards.

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 digital native chemists will embrace RDM and ELN as an organic part of their research.

Forschungsdatenmanagement (FDM) ist erforderlich, um wissenschaftlichen Fortschritt und das Sammeln von Daten zu fördern. Viele Fördergeldgeber verlangen FDM, da Forschung oft durch Steuergelder finanziert wird und daraus resultierende Daten nachhaltig für kommende Generationen hinterlegt werden sollten. In heutigen Laboren sind Papier‐Laborbücher allerdings noch immer gängige Praxis, und die Forschungsdaten werden oft in proprietären Dateiformaten ohne experimentellen Kontext gespeichert. Daten müssen über eine Rolle als bloßes Anhängsel von Publikationen hinauswachsen. Elektronische Laborbücher (ELN) und Laborinformationsmanagementsysteme (LIMS) ermöglichen es, Daten besser zu verwalten sowie Forschung und Veröffentlichung zu vereinfachen. Die in gutes FDM investierte Zeit zahlt sich später in vielerlei Hinsicht aus. Daher werden Mindestinformationsstandards (MI) für die Handhabung von Daten benötigt. Die Digitalisierung hält gerade Einzug in die Lehrpläne, sodass zukünftige Generationen von ChemikerInnen mit FDM und ELN‐Nutzung vertraut sein werden.

ATP-binding cassette (ABC) transporters are conserved in all kingdoms of life, where they transport substrates against a concentration gradient across membranes. Some ABC transporters are known to cause multidrug resistances in humans and are able to transport chemotherapeutics across cellular membranes. Similarly, BmrA, the ABC transporter of Bacillus subtilis, is involved in excretion of certain antibiotics out of bacterial cells. Screening of extract libraries isolated from fungi revealed that the C14 fatty acid myristic acid has an inhibitory effect on the BmrA ATPase as well as the transport activity. Thus, a natural membrane constituent inhibits the BmrA activity, a finding with physiological consequences as to the activity and regulation of ABC transporter activities in biological membranes.

The vision of NFDI4Chem is the digitalisation of all key steps in chemical research to support scientists in their efforts to collect, store, process, analyse, disclose and re-use research data. Measures to promote Open Science and Research Data Management (RDM) in agreement with the FAIR data principles are fundamental aims of NFDI4Chem to serve the chemistry community with a holistic concept for access to research data. To this end, the overarching objective is the development and maintenance of a national research data infrastructure for the research domain of chemistry in Germany, and to enable innovative and easy to use services and novel scientific approaches based on re-use of research data. NFDI4Chem intends to represent all disciplines of chemistry in academia. We aim to collaborate closely with thematically related consortia. In the initial phase, NFDI4Chem focuses on data related to molecules and reactions including data for their experimental and theoretical characterisation. This overarching goal is achieved by working towards a number of key objectives: Key Objective 1: Establish a virtual environment of federated repositories for storing, disclosing, searching and re-using research data across distributed data sources. Connect existing data repositories and, based on a requirements analysis, establish domain-specific research data repositories for the national research community, and link them to international repositories. Key Objective 2: Initiate international community processes to establish minimum information (MI) standards for data and machine-readable metadata as well as open data standards in key areas of chemistry. Identify and recommend open data standards in key areas of chemistry, in order to support the FAIR principles for research data. Finally, develop standards, if there is a lack. Key Objective 3: Foster cultural and digital change towards Smart Laboratory Environments by promoting the use of digital tools in all stages of research and promote subsequent Research Data Management (RDM) at all levels of academia, beginning in undergraduate studies curricula. Key Objective 4: Engage with the chemistry community in Germany through a wide range of measures to create awareness for and foster the adoption of FAIR data management. Initiate processes to integrate RDM and data science into curricula. Offer a wide range of training opportunities for researchers. Key Objective 5: Explore synergies with other consortia and promote cross-cutting development within the NFDI. Key Objective 6: Provide a legally reliable framework of policies and guidelines for FAIR and open RDM.

A novel electrochemical access to N , N ′-diarylhydrazines is developed using commercial anilines, a simple setup, and an ecologically efficient electrolyte system.