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Transforming Materials Science with ontologies, ELN, and LIMS: Semantic Web Solutions for Digitalization and Data Excellence

  • Following the new paradigm of materials development, design and optimization, digitalization is the main goal in materials sciences (MS) which imposes a huge challenge. In this respect, the quality assurance of processes and output data as well as the interoperability between applications following FAIR (findability, accessibility, interoperability, reusability) principles are to be ensured. For storage, processing, and querying of data in contextualized form, Semantic Web Technologies (SWT) are used since they allow for machine-understandable and human-readable knowledge representations needed for data management, retrieval, and (re)use. The project ‘platform MaterialDigital’ (PMD) is part of an initiative that aims to bring together and support interested parties from both industrial and academic sectors in a sustainable manner in solving digitalization tasks and implementing digital solutions. Therefore, the establishment of a virtual material data space and the systematization ofFollowing the new paradigm of materials development, design and optimization, digitalization is the main goal in materials sciences (MS) which imposes a huge challenge. In this respect, the quality assurance of processes and output data as well as the interoperability between applications following FAIR (findability, accessibility, interoperability, reusability) principles are to be ensured. For storage, processing, and querying of data in contextualized form, Semantic Web Technologies (SWT) are used since they allow for machine-understandable and human-readable knowledge representations needed for data management, retrieval, and (re)use. The project ‘platform MaterialDigital’ (PMD) is part of an initiative that aims to bring together and support interested parties from both industrial and academic sectors in a sustainable manner in solving digitalization tasks and implementing digital solutions. Therefore, the establishment of a virtual material data space and the systematization of the handling of hierarchical, process-dependent material data are focused. Core points to be dealt with are the development of agreements on data structures and interfaces implemented in distinct software tools and to offer users specific added values in their projects. Furthermore, the platform contributes to a standardized description of data processing methods in materials research. In this respect, selected MSE methods are ontologically represented which are supposed to serve as best practice examples with respect to knowledge representation and the creation of knowledge graphs used for material data. Accordingly, this presentation shows the efforts taken within the PMD project to store data in accordance with a testing standard compliant ontological representation of a tensile test of metals at room temperature (ISO 6892-1:2019-11). This includes the path from developing an ontology in accordance with the respective standard up to connecting the ontology and data. The semantic connection of the ontology and data leads to interoperability and an enhanced ability of querying. For further enhanced reusability of data and knowledge from synthesis, production, and characterization of materials, the PMD core ontology (PMDco) was developed as mid-level ontology in the field of MSE. The semantic connection of the tensile test ontology (TTO) to the PMDco leads to enhanced expressivity and interoperability. Moreover, as a best practice example, generation and acquisition of test data semantically connected to the ontology (data mapping) was realized by applying an electronic laboratory notebook (ELN). Corresponding tensile tests were performed by materials science students at university. This enabled a fully digitally integrated experimental procedure that can be transferred to other test series and experiments. In addition to facilitating the acquisition, analysis, processing, and (re)usability of data, this also raises the awareness of students with respect to data structuring and semantic technologies in the sense of education and training. The entire data pipeline is further seamlessly integrable in a laboratory information management system (LIMS). More specifically, the integration of semantic conceptualization and knowledge graphs may become essential parts in LIMS as this would be very beneficial. Therefore, some first approaches of SWT integration in LIMS will also be presented briefly.zeige mehrzeige weniger

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Autor*innen:Markus SchillingORCiD
Koautor*innen:Bernd Bayerlein, S. Bruns, H. Birkholz, P. von Hartrott, J. Waitelonis, J. W. Lau, Birgit Skrotzki
Dokumenttyp:Vortrag
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2024
Organisationseinheit der BAM:5 Werkstofftechnik
5 Werkstofftechnik / 5.2 Metallische Hochtemperaturwerkstoffe
DDC-Klassifikation:Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurwissenschaften und zugeordnete Tätigkeiten
Freie Schlagwörter:Electronic Lab Notebook; Material Life Cycle; Plattform Material Digital; Semantic Data; Tensile Test Ontology
Themenfelder/Aktivitätsfelder der BAM:Material
Material / Materialdesign
Veranstaltung:TMS Specialty Congress 2024
Veranstaltungsort:Cleveland, OH, USA
Beginndatum der Veranstaltung:16.06.2024
Enddatum der Veranstaltung:20.06.2024
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:25.06.2024
Referierte Publikation:Nein
Eingeladener Vortrag:Nein
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