TY - CONF A1 - Portella, Pedro Dolabella A1 - Skrotzki, Birgit A1 - Muth, Thilo T1 - Die Digitalisierung der Materialwissenschaft und Werkstofftechnik - ein Überblick N2 - Die Bereitstellung von zuverlässigen Werkstoffdaten stand für die Werkstoffprüfung seit dem 19. Jahrhundert in zentraler Stelle. Mit der zunehmender Digitalisierung unserer Gesellschaft gewinnt das Datenmanagement insbesondere im Hinblick auf die Modellierungs- und Simulationsaktivitäten an Bedeutung. In unserem Beitrag beschreiben wir die gegenwärtigen Aktivitäten in Deutschland – insbesondere die NFDI-MatWerk und die BMBF-Initiative MaterialDigital – sowie in Europa und Übersee. Abschließend heben wir die Auswirkungen auf die technische und akademische Aus- und Weiterbildung. T2 - DVM - Tagung Werkstoffprüfung CY - Online meeting DA - 03.12.2020 KW - Werkstoffdaten KW - Digitalisierung KW - Materialwissenschaft PY - 2020 AN - OPUS4-52044 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bayerlein, Bernd A1 - Hanke, T. A1 - Muth, Thilo A1 - Riedel, Jens A1 - Schilling, Markus A1 - Schweizer, C. A1 - Skrotzki, Birgit A1 - Todor, A. A1 - Moreno Torres, Benjami A1 - Unger, Jörg F. A1 - Völker, Christoph A1 - Olbricht, Jürgen T1 - A Perspective on Digital Knowledge Representation in Materials Science and Engineering JF - Advanced Engineering Materials N2 - The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples. In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge. KW - Data infrastructures KW - Digital representations KW - Digital workflows KW - Knowledge graphs KW - Materials informatics KW - Ontologies KW - Vocabulary providers PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-546729 DO - https://doi.org/10.1002/adem.202101176 SN - 1438-1656 SP - 1 EP - 14 PB - Wiley-VCH GmbH CY - Weinheim AN - OPUS4-54672 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Valdestilhas, Andre A1 - Bayerlein, Bernd A1 - Moreno Torres, Benjamin A1 - Jan Zia, Ghezal Ahmad A1 - Muth, Thilo T1 - The Intersection Between Semantic Web and Materials Science JF - Advanced Intelligent Systems N2 - The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE. KW - Linked open data KW - Materials science KW - Ontology KW - Semantic web PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-575506 DO - https://doi.org/10.1002/aisy.202300051 PB - Wiley-VCH GmbH CY - Weinheim AN - OPUS4-57550 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -