Towards Structured Data Spaces: Prototypical Application of Semantic Technologies as a Driver for Innovation in Materials Science

  • In the pursuit of advancing development and digitalization within materials science, ensuring quality assurance, interoperability, and adherence to FAIR principles is significant. To address these aspects, semantic technologies are employed for storage, processing, and contextualization of data, offering machine-actionable and human-readable knowledge representations crucial for data management. This presentation showcases the prototypical application of generic approaches of knowledge representation in materials science. It includes the design and documentation of graph patterns that may be compiled into rule-based semantic shapes. The development and application of the PMD Core Ontology 3.0 (PMDco 3.0) tailored for materials science is highlighted. Its integration into daily lab life is demonstrated through its functional incorporation into electronic lab notebooks (ELN). Examples of material processing and standardized mechanical testing illustrate how knowledge graph operationsIn the pursuit of advancing development and digitalization within materials science, ensuring quality assurance, interoperability, and adherence to FAIR principles is significant. To address these aspects, semantic technologies are employed for storage, processing, and contextualization of data, offering machine-actionable and human-readable knowledge representations crucial for data management. This presentation showcases the prototypical application of generic approaches of knowledge representation in materials science. It includes the design and documentation of graph patterns that may be compiled into rule-based semantic shapes. The development and application of the PMD Core Ontology 3.0 (PMDco 3.0) tailored for materials science is highlighted. Its integration into daily lab life is demonstrated through its functional incorporation into electronic lab notebooks (ELN). Examples of material processing and standardized mechanical testing illustrate how knowledge graph operations enhance ELN capabilities, providing a generalizable unified approach for managing diverse experimental data from different sources with automation potentials.zeige mehrzeige weniger

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Metadaten
Autor*innen:Markus SchillingORCiD
Koautor*innen:Bernd Bayerlein, P. von Hartrott, J. Waitelonis, H. Birkholz, Birgit SkrotzkiORCiD
Dokumenttyp:Vortrag
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2025
Organisationseinheit der BAM:5 Werkstofftechnik
5 Werkstofftechnik / 5.2 Metallische Hochtemperaturwerkstoffe
DDC-Klassifikation:Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurwissenschaften und zugeordnete Tätigkeiten
Freie Schlagwörter:Data Integration; Data Interoperability; Digitalization; Plattform MaterialDigital; Semantic Data
Themenfelder/Aktivitätsfelder der BAM:Material
Material / Advanced Materials
Veranstaltung:TMS Specialty Congress 2025
Veranstaltungsort:Anaheim, CA, USA
Beginndatum der Veranstaltung:15.06.2025
Enddatum der Veranstaltung:19.06.2025
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:17.06.2025
Referierte Publikation:Nein
Eingeladener Vortrag (wissenschaftliche Konferenzen):Nein
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