TY - CONF A1 - Bayerlein, Bernd T1 - Platform MaterialDigital Core Ontology (PMDco): A Community Driven Mid-Level Ontology in the MSE Domain N2 - Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific. The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications. T2 - Patents4Science CY - Berlin, Germany DA - 05.10.2023 KW - Knowledge Representation KW - Semantic Interoperability KW - FAIR data management KW - Knowledge graph and ontologies KW - PMD Core Ontology PY - 2023 AN - OPUS4-58507 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - News from the working area - Semantic Interoperability N2 - This presentation provides a comprehensive overview of recent developments and the current status within the Semantic Interoperability work area, with a particular emphasis on the advancements related to the Platform MaterialDigital Core Ontology (PMDco). The presentation will delve into the collaborative and community-supported curation process that has been instrumental in shaping PMDco. Additionally, we will introduce the innovative Ontology Playground, showcasing its role in fostering experimentation and exploration within the realm of ontology development. T2 - MaterialDigital Vollversammlung CY - Karlsruhe, Germany DA - 21.09.2023 KW - Semantic Representation KW - FAIR data management KW - Semantic Interoperability KW - Knowledge graph and ontologies KW - PMD Core Ontology KW - MaterialDigital PY - 2023 AN - OPUS4-58422 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd A1 - Schilling, Markus A1 - Z.-Jan, G.-A. A1 - Hanke, T. A1 - v. Hartrott, P. A1 - Fliegener, S. A1 - Kryeziu, J. A1 - Waitelonis, J. A1 - Sack, H. A1 - Skrotzki, Birgit T1 - Adopting FAIR data practices in materials science: Semantic representation of a quantitative precipitation analysis N2 - Many metallic materials gain better mechanical properties through controlled heat treatments. For example, in age-hardenable aluminium alloys, the strengthening mechanism is based on the controlled formation of nanometre-sized precipitates, which represent obstacles to dislocation movement and consequently increase the strength. Precise tuning of the material microstructure is thus crucial for optimal mechanical behaviour under service condition of a component. Therefore, analysis of the microstructure, especially the precipitates, is essential to determine the optimum parameters for the interplay of material and heat treatment. Transmission electron microscopy (TEM) is utilized to identify precipitate types and orientations in the first step. Dark-field imaging (DF-TEM) is often used to image the precipitates and thereafter quantify their relevant dimensions. Often, these evaluations are still performed by manual image analysis, which is very time-consuming and to some extent also poses reproducibility problems. Our work aims at a semantic representation of an automatable digital approach for this material specific characterization method under adaption of FAIR data practices. Based on DF-TEM images of different precipitation states of a wrought aluminium alloy, the modularizable, digital workflow of quantitative analysis of precipitate dimensions is described. The integration of this workflow into a data pipeline concept will also be discussed. Using ontologies, the raw image data, their respective contextual information, and the resulting output data of the quantitative image analysis can be linked in a triplestore. Publishing the digital workflow and the ontologies will ensure data reproducibility. In addition, the semantic structure enables data sharing and reuse for other applications and purposes, demonstrating interoperability. T2 - FEMS EUROMAT 2023 CY - Frankfurt a. M., Germany DA - 03.09.2023 KW - Semantic Representation KW - FAIR data management KW - Quantitative Precipitation Analysis KW - Knowledge graph and ontologies PY - 2023 AN - OPUS4-58199 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bruns, Sebastian A1 - Bayerlein, Bernd A1 - Grönewald, Mathias A1 - Kryeziu, Jeonna A1 - Schilling, Markus A1 - Waitelonis, Jörg A1 - Portella, Pedro Dolabella A1 - Durst, Karsten 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 -