In chemistry and its related sciences, large amounts of experimental and analytical data are generated and evaluated by scientists every day. Here, advancing digitalization offers the possibility of documenting and storing these data in an appropriate way. However, to ensure sustainable research a reasonable research data management (RDM) is crucial. [1] Good RDM is a powerful tool that facilitates to improve the research data lifecycle (see figure [2]) and to meet the FAIR data principles (findable, accessible, interoperable, reusable). [3] Getting started with RDM in chemical research can be challenging. Therefore, the consortium NFDI4Chem (National Research Data Infrastructure for Chemistry, Germany) was formed aiming to support scientists in the digitalization process by providing a national infrastructure. [4] A key step for reaching this goal is the use of electronic laboratory notebooks (ELN) to document experiments and data repositories to publish research data. Within NFDI4Chem, the open source software Chemotion, consisting of an ELN and a repository, is developed and provided as a tool enabling digitalization in research and teaching. [5, 6] In this talk, we introduce the consortium NFDI4Chem in general, discuss its necessity in the digital transformation, and present its function, goals, and various tasks. In the second part of the talk, the main focus is on the software Chemotion. Here, the ELN and repository are shown in detail, accompanied by examples of successful implementation in chemical research.

In view of the increasing digitization of research and the use of data-intensive measurement and analysis methods, research institutions and their staff are faced with the challenge of documenting a constantly growing volume of data in a comprehensible manner, archiving them for the long term, and making them available fordiscovery andre-use by others in accordance with the FAIR principles[1]. At BAM, we aim to facilitate the integration of research data management (RDM)strategies duringthe whole research cyclefrom the creation and standardized description of materials datasetsto theirpublication in open repositories. To this end, we presentthe BAM Data Store, a central system for internal RDM that fulfills the heterogenous demands of material science and engineering labs. The BAM Data Store is based on openBIS, an open-source softwaredeveloped by the ETH Zurichthat has originally been created for life science laboratories but that has since been deployed in a variety of research domains [2]. The software offersa browser-based user interface for the digital representation of lab inventoryentities(e.g.,samples, chemicals, instruments,and protocols) and an electronic lab notebookfor the standardized documentation of experimentsand analyses.To investigate whether openBIS is a suitable framework for the BAM Data Store, we carried out a pilot phase during which five research groups with employees from 16 different BAM divisions were introduced to the software. The pilot groups were chosen to represent a diverse array of domain use cases and RDM requirements (e.g., small vs big data volume, heterogenous vs structured data types) as well as varying levels of prior IT knowledgeon theusers’ side. We further conducted a self-assessment of our institutional RDM strategies and services using the RISE-DE model to take stock of the current situation and identify areas for improvement and development[3].Overall, the results of the pilot phase are promising: While the creation of custom data structures and metadata schemas can be time-intensive and requires the involvement of domain experts, the system offers specific benefits in the form ofasimplified documentation and automation of research processes, as well as constituting a basis for data-driven analysis.In this way, heterogeneous research workflows in various materials science research domains could be implemented,from the synthesis and characterization of nanomaterials to non-destructive 3D imaging and the monitoring of engineering structures.In addition to the technical deployment and the development of domain-specific metadata standards, the pilot phase also highlighted the need for suitable institutional infrastructures, processes,and role models. An institute-wide rollout of the BAM Data Store is currently being planned.

Skills and perspective to work with software and data are increasingly important as we generate more data. This has only become more important as code and software development forms the basis of so much of our work. With the emergence of our ability to generate increasing amounts of data, research and work in almost every domain has a data and computational component, including the whole new field of data science. Therefore The Carpentries want to build skills and a community to create training in the gaps, offer hands-on workshops and create lesson materials with a supporting community. The Carpentries is a non-profit organization staffed mostly by volunteers. The Carpentries’ vision is to share data and science skills with researchers and librarians while focusing on community building that is, building capacity for teaching and learning at the local level.