TY - CONF A1 - Schilling, Markus T1 - Digital Transformation in Materials Science: PMD Core Ontology (PMDco) 3.0 – Patterns & Applications N2 - The digitalization of Materials Science and Engineering (MSE) demands standardized, interoperable approaches for representing complex experimental and simulation data. To address this challenge, the Platform MaterialDigital Core Ontology (PMDco) provides a mid-level semantic framework that bridges high-level ontologies and domain-specific terminologies. PMDco version 3.0, recently released, introduces significant enhancements based on a full alignment with the Basic Formal Ontology (BFO) as standardized in ISO/IEC 21838-2. This alignment ensures conceptual consistency and facilitates integration across heterogeneous data sources while enabling FAIR-compliant workflows. First addressing the idea behind a mid-level ontology in MSE, this presentation emphasizes its role in harmonizing diverse data models and supporting machine-actionable knowledge representation. New features and design patterns introduced in PMDco 3.0 will be highlighted, which strengthen interoperability and provide reusable modeling structures for common MSE concepts. Practical applications and prototype implementations will be discussed. PMDco has been developed through active community involvement and its future evolution relies on continued collaboration and discussion within the MSE community. Participation is strongly encouraged to ensure that PMDco remains relevant, comprehensive, and widely adopted. More information and opportunities to contribute can be found at materialdigital.de and github.com/materialdigital/core-ontology. T2 - VMAP User Forum 2026 CY - Sankt Augustin, Germany DA - 24.02.2026 KW - Semantic Technology KW - Knowledge Graph KW - PMD Core Ontology KW - Semantic Pattern KW - Machine-actionability PY - 2026 AN - OPUS4-65574 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Advancing Digital Workflows in Materials Science: The Role of PMDco in Data Integration and Semantic Representation N2 - The field of Materials Science and Engineering (MSE) is undergoing a transformative shift towards digitalization, emphasizing the need for structured and interoperable data management. The Platform MaterialDigital Core Ontology (PMDco), now in version 3.0, addresses these challenges by providing a robust mid-level semantic framework. PMDco bridges the gap between abstract high-level ontologies, such as the Basic Formal Ontology (BFO) standardized in ISO/IEC 21838-2, and highly specific domain terminologies to ensure consistency and interoperability across diverse MSE applications. Developed through MSE community-based curation, PMDco facilitates the integration of real-world data from experiments, simulations, and industrial processes. This presentation will explore PMDco's role in enabling advanced digital workflows and its integration into demonstrators within the Platform MaterialDigital (PMD) initiative. Highlighted use cases include the semantic representation of tensile test data in compliance with ISO 6892-1:2019-11, utilizing the corresponding tensile test ontology (TTO) built on PMDco. Through an electronic laboratory notebook (ELN), data from experiments performed by undergraduate students were transformed into machine-actionable knowledge graphs, demonstrating the potential for education and fully digitalized experimental procedures. Additionally, a possible extension of PMDco as a linking point for semantically representing simulation data will be presented, aligning with the focus of VMAP. This includes linking experimental, simulation, and computational datasets to create comprehensive, FAIR-compliant knowledge ecosystems. By showcasing best practices in data acquisition, semantic integration, and knowledge graph generation, this presentation underscores PMDco’s versatility and its critical role in advancing digital MSE workflows. T2 - VMAP User Forum 2025 CY - Sankt Augustin, Germany DA - 18.02.2025 KW - Semantic Data KW - Data Integration KW - Digitalization KW - Data Interoperability KW - PMD Core Ontology PY - 2025 AN - OPUS4-62607 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Digital Transformation in Materials Science through Semantic Technologies and Knowledge Graphs N2 - The field of materials science is undergoing a transformative shift driven by digitalization. In this respect, semantic and AI technologies are paving the way for advancements in materials development, design, and optimization while leaping towards an Industry 4.0 environment. Addressing the dual challenges of quality assurance and data interoperability, this presentation examines the integration of semantic technologies and knowledge representation methods. By adhering to FAIR principles, this approach enhances data management, storage, and reuse. That way, both machine-actionable and human-understandable data structures crucial for digital research environments are fostered. This presentation focuses on the ‘platform MaterialDigital’ (PMD) initiative, which aims to support efforts from both industrial and academic sectors to solve digitalization challenges and implement sustainable digital solutions. Besides establishing structures to create virtual material data spaces, PMD develops solutions for systematizing and unifying the handling of hierarchical, process-dependent material data. Semantic technologies play a crucial role in digitalization efforts as they enable the storage, processing, and querying of data in a contextualized form. Therefore, the development and prototypical application of the PMD Core Ontology 3.0 (PMDco 3.0) tailored for materials science is highlighted. This includes the design and documentation of graph patterns that may be compiled into rule-based semantic shapes. Its integration into daily lab life is demonstrated through its application to electronic lab notebooks (ELN). This illustrates potentials of standardized protocols and automation-ready solutions for managing diverse experimental data across different sources. Outlining best practices and illustrating the possibilities that semantic technologies bring to modern labs, examples from materials processing and mechanical testing will underscore how knowledge graphs bridge the gap between data and decision-making in materials science, with potential for increased productivity and streamlined workflows across the field. T2 - Materials Week 2025 CY - Frankfurt am Main, Germany DA - 03.04.2025 KW - Semantic Data KW - Data Integration KW - Digitalization KW - Data Interoperability KW - PMD Core Ontology PY - 2025 AN - OPUS4-62866 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Plattform MaterialDigital (PMD): Konsortium, Zielsetzung, Core Ontology N2 - Die Materialwissenschaft und Werkstofftechnik (MSE) durchläuft derzeit eine digitale Transformation, die ein strukturiertes und interoperables Datenmanagement erfordert. Die Plattform MaterialDigital (PMD) adressiert diese Herausforderungen mit der PMD Core Ontology (PMDco), die inzwischen in Version 3.0 vorliegt. Diese mittlere Ontologieebene schafft eine Brücke zwischen abstrakten Top-Level-Ontologien wie der ISO/IEC 21838-2 standardisierten Basic Formal Ontology (BFO) und spezifischen domänenspezifischen Vokabularen. Ziel ist die Förderung semantischer Interoperabilität sowie die Nachvollziehbarkeit und Wiederverwendbarkeit von Daten entlang der gesamten Wertschöpfungskette in der MSE. Die Präsentation gibt einen Überblick über die Zielsetzung des PMD-Konsortiums, die Community-getriebene Entwicklung der PMDco sowie ihre Rolle in digitalen Workflows und Demonstratoren. Praxisbeispiele beinhalten die semantische Modellierung von Zugversuchen gemäß ISO 6892-1:2019-11 mithilfe der darauf aufbauenden Zugversuch-Ontologie (TTO) sowie die Umwandlung experimenteller Daten von Studierenden in maschinenlesbare Wissensgraphen über eine elektronische Laborbuch-Pipeline. Zudem wird die Ontologieentwicklung durch NLP-gestützte Ansätze (z. B. für Mikroskopie) sowie die Harmonisierung heterogener Datenquellen (z. B. im Orowan-Demonstrator) vorgestellt. Damit leistet PMDco einen entscheidenden Beitrag zur digitalen Zukunft der Materialforschung. T2 - Abschlusskolloquium LeBeDigital CY - Berlin, Germany DA - 04.06.2025 KW - Semantic Data KW - Data Integration KW - Digitalisierung KW - Digitale Transformation KW - Plattform MaterialDigital PY - 2025 AN - OPUS4-63295 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Semantic Technologies for Digital Transformation in Materials Science: From PMDco to Prototypical Applications N2 - The digital transformation of Materials Science and Engineering (MSE) is accelerating the adoption of structured, interoperable, and FAIR data practices, in particular with respect to an advanced research data management. Semantic technologies play a pivotal role in this transformation, as the enable the integration, contextualization, and automation of diverse data sources across experimental, computational, and simulation domains. Central to these efforts is the Platform MaterialDigital Core Ontology (PMDco), now in version 3.0, which provides a robust mid-level semantic framework tailored for MSE. PMDco bridges abstract high-level ontologies, such as the Basic Formal Ontology (BFO) standardized in ISO/IEC 21838-2, with domain-specific terminologies to ensure consistency and interoperability across applications. This presentation explores the application of PMDco and its integration into workflows within the Platform MaterialDigital (PMD) initiative. Through its deployment in electronic laboratory notebooks (ELNs), PMDco enables semantic representation of experimental data, such as tensile test results compliant with ISO 6892-1:2019-11, transforming them into machine-actionable knowledge graphs. Prototypical implementations demonstrate how semantic technologies enhance laboratory processes, improve data reuse, and streamline documentation which offers opportunities for automation and education. Further extending its versatility, PMDco serves as a linking point for semantically representing simulation data, enabling comprehensive integration of experimental and computational datasets. This creates structured data spaces that support advanced digital workflows. Beyond PMDco, the presentation highlights the design of graph patterns and semantic shapes, showcasing generalizable methods for managing diverse data in MSE being based on data structuring and formatting. By presenting best practices in ontology development, data acquisition, and knowledge graph generation, this talk underscores the transformative potential of semantic technologies in MSE. It offers a forward-looking perspective on the role of structured data spaces as a driver for innovation, ensuring that materials science continues to advance through rigorous, interoperable, and automated digital methodologies. T2 - FEMS Euromat 2025 CY - Granada, Spanien DA - 14.09.2025 KW - Semantic Data KW - Data Integration KW - Digitalization KW - Data Interoperability KW - PMD Core Ontology KW - Graph Patterns PY - 2025 AN - OPUS4-64165 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Data-Driven Materials Science: Reproducibility and Standardization N2 - Advancing development and digitalization in materials science requires to focus on quality assurance, interoperability, and compliance with FAIR principles. Semantic technologies offer effective solutions for these challenges by enabling the storage, processing, and contextualization of data in machine-actionable and human-readable formats – essential for robust data management. This presentation highlights the PMD Core Ontology 3.0 (PMDco 3.0), developed specifically for the field of materials science and engineering, and its implementation within generic knowledge representation frameworks. Demonstrators such as standardized mechanical testing, material processing workflows, and the Orowan Demonstrator exemplify the ontology’s practical applications. The use of graph patterns, able to be compiled into rule-based semantic shapes, supports a unified and automated approach to managing heterogeneous experimental data across domains. T2 - Persson Group Seminar CY - Berkeley, CA, USA DA - 23.06.2025 KW - Semantic Data KW - Data Integration KW - Digitalization KW - Data Interoperability KW - PMD Core Ontology KW - Graph Patterns PY - 2025 AN - OPUS4-63484 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - On Shared Vocabulary, Ontologies, Semantic Data and Prototype Applications N2 - The advancement of development and digitalization in materials science necessitates rigorous quality assurance, interoperability, and adherence to FAIR principles. Semantic technologies contribute to these objectives by facilitating the structured storage, processing, and contextualization of data, yielding machine-actionable and human-interpretable knowledge representations vital for modern 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). In this respect, a possible integration of semantic technologies into openBIS is presented. The openBIS system is usable as a central data storage system that may be complimented by semantic annotation of data to enhance data contextualization and automation. Graph-based knowledge representations and rule-based semantic shapes are shown which were developed alongside the PMD Core Ontology 3.0 (PMDco 3.0) and can enrich openBIS functionalities. Practical examples from material processing and mechanical testing illustrate how semantic extensions of openBIS enable machine-actionable, interoperable, and reusable research data, paving the way for a unified, ontology-driven laboratory data ecosystem. T2 - openBIS User Group Meeting (openBIS UGM) CY - Berlin, Germany DA - 22.09.2025 KW - Semantic Data KW - Data Integration KW - Digitalization KW - OpenBIS KW - Ontologies KW - Graph Patterns PY - 2025 AN - OPUS4-64307 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Vom Experiment zur semantischen Wissensrepräsentation: Datenstandards und Interoperabilität in der Materialcharakterisierung N2 - Im Zeitalter der digitalen Transformation rückt die strukturierte Erfassung und semantische Verknüpfung von Materialcharakterisierungsdaten immer stärker in den Fokus, um eine effiziente Nutzung über Disziplin- und Projektgrenzen hinweg zu gewährleisten. Dabei bilden etablierte Datenstandards und semantische Technologien sowie Ontologien die Grundlage für eine nach FAIR-Kriterien aufgebaute Dateninfrastruktur, die sowohl maschinenlesbare als auch nachvollziehbare Wissensrepräsentationen ermöglicht. In dieser Präsentation sollen Prinzipien interoperabler Datenarchitekturen erläutert werden, wobei auf die Bedeutung normkonformer Modelle und semantischer Konzeptualisierungen eingegangen wird. Dabei wird der steigende Bedarf an verlässlichen, reproduzierbaren und wiederverwendbaren Daten im Bereich der Materialwissenschaft und Werkstofftechnik adressiert, der insbesondere die Materialcharakterisierung und Werkstoffprüfung vor neue Herausforderungen stellt. Hinsichtlich der angestrebten Möglichkeiten zum erleichterten Datenaustausch kommen einheitlichen Datenformaten und -beschreibungen eine besondere Bedeutung zu. Anhand ausgewählter Publikationen und Demonstratoren wird aufgezeigt, wie Ontologien als verbindende Zwischenschicht unterschiedliche Material- und Verfahrensdomänen konsistent abbilden und zusammenführen können. Ein praktischer Anwendungsfall verdeutlicht die RDF-basierte Repräsentation von Zugversuchsdaten und deren Einbettung in ein Triple-Store-Datenbank-Umfeld. Hierbei fließen Erfahrungen aus der Entwicklung und Anwendung der PMD Core Ontology (PMDco) sowie normenkonformer Ontologien (z.B. Tensile Test Ontology, TTO) ein, welche im Rahmen des Projektes Plattform MaterialDigital (PMD, materialdigital.de) erstellt und betrachtet wurden. Darüber hinaus werden weitere methodische Ansätze und Entwicklungen aus diesem Projekt illustriert. T2 - Tagung Werkstoffprüfung 2025 CY - Dresden, Germany DA - 27.11.2025 KW - Wissensrepräsentation KW - Ontologie KW - Werkstoffprüfung KW - Digitale Transformation KW - Interoperabilität PY - 2025 AN - OPUS4-64944 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Towards Structured Data Spaces: Prototypical Application of Semantic Technologies as a Driver for Innovation in Materials Science N2 - 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 operations enhance ELN capabilities, providing a generalizable unified approach for managing diverse experimental data from different sources with automation potentials. T2 - TMS Specialty Congress 2025 CY - Anaheim, CA, USA DA - 15.06.2025 KW - Semantic Data KW - Data Integration KW - Digitalization KW - Data Interoperability KW - Plattform MaterialDigital PY - 2025 AN - OPUS4-63401 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Semantic Technologies in Action: Integrating Mechanical and Microstructure Data in MSE N2 - Semantic technologies (ST) are a powerful tool for storing, processing, and querying data in a contextualized and interoperable manner. They enable machine-actionable and human-readable knowledge representations essential for advanced data management, retrieval, and reuse. As one of the key factors within the frame of the collaborative project platform MaterialDigital (PMD), the establishment of a virtual material data space and the semantic modeling of hierarchical, process-dependent material data is aimed at to serve as best-practice examples of knowledge representation through ontologies and knowledge graphs. In this presentation, the application of ST to a specific use case from the field of materials sciences and engineering (MSE) is demonstrated: the integration and analysis of data related to a 2000 series age-hardenable aluminum alloy. By semantically representing mechanical and microstructural data obtained from tensile tests and dark-field transmission electron microscopy across various aging times, an expandable knowledge graph was constructed that is aligned with the PMD Core Ontology (PMDco) and enriched through the Tensile Test (TTO) and Precipitate Geometry Ontologies. This semantically integrated dataset enables advanced analytical capabilities via SPARQL queries and reveals microstructure–property relationships consistent with the well-known Orowan mechanism. The approach highlights the potential of semantic data integration to support FAIR data principles and to foster a more data-centric and interoperable research infrastructure in MSE. T2 - MSE Research Data Forum 2025 CY - Siegburg, Germany DA - 08.07.2025 KW - Semantic Data KW - Data Integration KW - Digitalization KW - Data Interoperability PY - 2025 AN - OPUS4-63666 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -