TY - CONF A1 - Bruns, Sebastian T1 - Digitalizing a lab course for undergraduate students: ELN, ontology, data management N2 - We report about a joint project aiming at the digitalization of a lab course in materials testing. The undergraduate students were asked to prepare samples of a precipitation hardened aluminum alloy and characterize them using hardness and tensile tests. In a first step, we developed the frames for the digital labor notebook using eLabFTW. The primary data and the relevant metadata of each run were saved in a central database and made available for analysis and report issues. The whole set of results produced in a course was made available in the database. This database can be improved and serve as an open repository for data on this specific alloy. The logical frame for the joint project was provided by the PMD Core Ontology (PMDco), a mid-level ontology that enables the representation and description of processes and process chains in an MSE-specific manner, ensuring full traceability of generated data. For the digitalization of this lab course, the tensile test ontology (TTO) was applied which is designed as a module of the PMDco using strongly related semantic concepts. T2 - FEMS EUROMAT 2023 CY - Frankfurt a. M., Germany DA - 03.09.2023 KW - Electronic Lab Notebook KW - FAIR data management KW - Digtial Representation KW - Knowledge graph and ontologies PY - 2023 AN - OPUS4-58207 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - Towards interoperability: Digital representation of a material specific characterization method N2 - Certain metallic materials gain better mechanical properties through controlled heat treatments. In age-hardenable aluminum alloys, the strengthening mechanism is based on the controlled formation of nanometer sized precipitates, which hinder dislocation movement. Analysis of the microstructure and especially the precipitates by transmission electron microscopy allows identification of precipitate types and orientations. Dark-field imaging is often used to image the precipitates and quantify their relevant dimensions. The present work aims at the digital representation of this material-specific characterization method. Instead of a time-consuming, manual image analysis, a digital approach is demonstrated. The integration of an exemplary digital workflow for quantitative precipitation analysis into a data pipeline concept is presented. Here ontologies enable linking of contextual information to the resulting output data in a triplestore. Publishing digital workflow and ontologies ensures the reproducibility of the data. The semantic structure enables data sharing and reuse for other applications and purposes, demonstrating interoperability. T2 - TMS - 7th World Congress on Integrated Computational Materials Engineering (ICME) CY - Orlando, Florida, USA DA - 21.05.2023 KW - Ontology KW - Semantic Interoperability KW - Digtial Representation KW - Data Management KW - Reproducibility KW - FAIR PY - 2023 AN - OPUS4-57548 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - Digital Transformation in Materials Science:Insights from Platform MaterialDigital N2 - In the digital transformation of materials science and engineering, existing processes are being closely examined to optimize and extend them using technologies such as the Semantic Web, while adhering to the FAIR principles. The challenge is to identify and adapt these technologies to significantly improve daily operations, covering the entire cycle of data generation, collection, storage to its processing and use. This presentation presents different approaches developed within the Platform MaterialDigital (PMD) and related initiatives, each addressing specific challenges of digitalization and demonstrating their benefits. These will be illustrated by a case study on age-hardenable aluminium alloys in different aging states, based on a comprehensive dataset of microstructural and mechanical properties. In this context, ontologies are essential for organizing data into interoperable semantic structures, thereby enabling the representation of concepts and their relationships. The PMD Core Ontology (PMDco) serves as a higher semantic layer that connects domain-specific ontologies [1]. The PMDco provides MSE-specific bridging concepts that enhance data mapping and integration capabilities. This approach facilitates the linking of results from natural language processing of a corpus of microscopy abstracts, which supported the development of a microscopy ontology. In addition, the presentation highlights how modular, digital workflows can improve the reproducibility of transmission electron microscopy image processing and analysis [2]. It also shows how freely available mechanical and microstructural datasets are semantically integrated and made searchable through PMDco, facilitating correlation analysis [3]. Looking ahead, the integration of these components has the potential to advance and sustain MSE practices. T2 - MSE Congress 2024 - Materials Science and Engineering CY - Darmstadt, Germany DA - 24.09.2024 KW - Semantic Interoperability KW - FAIR data management KW - Digtial Representation PY - 2024 AN - OPUS4-61137 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -