Electronic Lab Notebooks and Laboratory Inventory Management Systems (ELN-LIMS) are state of the art in the life sciences and biological laboratories. In Material Science and Engineering (MSE) laboratories, electronic lab notebooks and digital data recording facilities exist but have to date not reached the level of professionalism that can be found in other disciplines, apart from specialized accredited laboratories. Typically, experimental data is recorded and (pre-)processed using the (often proprietary) software delivered with a specific testing device and then compiled, evaluated, and reported by working with scripts, spreadsheets, and documents in the directory structure of a filesystem. This approach usually impedes the capability to easily compare, interlink and validate the data by requiring many steps of manual data handling and processing. Furthermore, this approach increases the risk of introducing errors as well as complicates the traceability and replicability of results.

As part of their digitalization roadmaps, Fraunhofer IWM and BAM have evaluated the open source ELN-LIMS software openBIS for the usage in MSE laboratories. openBIS combines a data management system with an ELN where researchers and technicians can document experiments in a standardized way using sets of custom metadata properties. Experiments can further be linked to inventory entities such as measurement devices and standard operating procedures, thus allowing for the digital representation of workflows. The focus of the evaluation was to determine if a general purpose ELN-LIMS like openBIS , although stemming from life sciences, can be used as a central data platform for internal research data management, linking together typical experimental MSE investigations and procedures. The spectrum of evaluated cases comprised a wide range starting from mechanical specimen preparation, tensile- and fatigue testing, metallography, and ranging to more advanced cases like synthesis and characterization of nanomaterials, additive manufacturing, CT for non-destructive testing, and structural health management. The assumption for the evaluation was that multiple groups with their domain expertise and group-specific equipment and workflows, participate in a project where members of every group contribute to the overall project dataset.

The results of the evaluation are very promising. After an initial setup and training by the ETH Zürich Scientific IT Services team which also develops and maintains the software, selected pilot groups (BAM) and a dedicated project team (Fraunhofer IWM) customized the software according to their needs by developing appropriate metadata schemes and data models. This bottom-up approach quickly led to usable custom installations that fit the needs of the heterogenous scientific research groups. The system provides the basis for describing data with rich metadata in accordance with the FAIR data principles, thus preparing it for subsequent integration into public repositories or transmission to customers. The data generated in the test cases adheres to the FAIR principles better than previous formats and procedures. However, the pilot phase also showed the overlaps between groups which would benefit from harmonization within and across institutes, thus further highlighting the need to liaise with the ongoing development and sharing of FAIR (meta)data standards in the MSE community.