TY - CONF A1 - Beygi Nasrabadi, Hossein A1 - Chen, Yue A1 - Hanke, T. A1 - von Hartrott, P. A1 - Skrotzki, Birgit T1 - Domain-level ontology formulation based on the Platform Material Digital (PMD) ontology: case study Brinell hardness N2 - A large amount of publicly available data is reproduced every day in the field of materials science, while these kind of material data can have different formats and types like paper-type publications, standards, datasheets or isolated datasets in repositories. However, gathering a specific library from such extensive and diverse material data is always challenging for the materials scientists and engineers, since the time-related limitations are not allowed to fully access the large publicly available databases; search across these disparate databases, manage the large volumes of heterogeneous datasets, and integrate data from multiple sources. To address these challenges and make data findable, accessible, interoperable, and reusable (FAIR), an efficient data management system is necessary to build comprehensive, documented, and connected data spaces in the future. A formal standardized knowledge representation through an ontology can address such problems and make data more available and interoperable between related domains. Ontology can also rich machine processable semantic descriptions that increases the performance of scientific searches. In this regard, the Platform MaterialDigital (PMD) is currently working on developing a high-level ontology for the materials and material related processes. For example, in one of the PMD projects of “KupferDigital”, we will try to develop a data ecosystem for digital materials research based on ontology-based digital representations of copper and copper alloys. As a case study, this paper describes the methodology for ontology development of Brinell hardness, based on PMD core ontology. The methodology we describe includes the following steps; gathering the required domain terminology from different resources like standards (DIN EN ISO 6506-1) and test reports, representing the performance of a standard-conformant hardness test and the treatment of the recorded values up to a “reportable” hardness value for a material, designing the process chain according to the semantic technologies, and developing a domain-level ontology of Brinell hardness based on PMD ontology semantic formalization. Apart the mentioned methodology, some interesting tools and methods were introduced and ontology design challenges and possible solutions for modelling materials and processes were discussed. Furthermore, a dataset from the Brinell hardness measurement of cast copper samples is prepared for testing the query process. T2 - MSE 2022 CY - Darmstadt, Germany DA - 27.09.2022 KW - Copper KW - Materials Science KW - Ontology KW - Platform MaterialDigital (PMD) KW - Brinell hardness PY - 2022 AN - OPUS4-56092 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Chen, Yue A1 - Schilling, Markus A1 - von Hartrott, P. A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit A1 - Olbricht, Jürgen T1 - Ontopanel: A Tool for Domain Experts Facilitating Visual Ontology Development and Mapping for FAIR Data Sharing in Materials Testing JF - Integrating Materials and Manufacturing Innovation N2 - In recent years, the design and development of materials are strongly interconnected with the development of digital technologies. In this respect, efficient data management is the building block of material digitization and, in the field of materials science and engineering (MSE), effective solutions for data standardization and sharing of different digital resources are needed. Therefore, ontologies are applied that represent a map of MSE concepts and relationships between them. Among different ontology development approaches, graphical editing based on standard conceptual modeling languages is increasingly used due to its intuitiveness and simplicity. This approach is also adopted by the Materials-open-Laboratory project (Mat-o-Lab), which aims to develop domain ontologies and method graphs in accordance with testing standards in the field of MSE. To suit the actual demands of domain experts in the project, Ontopanel was created as a plugin for the popular open-source graphical editor diagrams.net to enable graphical ontology editing. It includes a set of pipeline tools to foster ontology development in diagrams.net, comprising imports and reusage of ontologies, converting diagrams to Web Ontology Language (OWL), verifying diagrams using OWL rules, and mapping data. It reduces learning costs by eliminating the need for domain experts to switch between various tools. Brinell hardness testing is chosen in this study as a use case to demonstrate the utilization of Ontopanel. KW - Materials Testing KW - Ontology KW - Visual ontology development KW - Data mapping KW - FAIR PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-560339 DO - https://doi.org/10.1007/s40192-022-00279-y SP - 1 EP - 12 PB - Springer AN - OPUS4-56033 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Ontology-oriented modeling of the Vickers hardness knowledge graph N2 - This research deals with the development of the Vickers hardness knowledge graph, mapping the example dataset in them, and exporting the data-mapped knowledge graph as a machine-readable Resource Description Framework (RDF). Modeling the knowledge graph according to the standardized test procedure and using the appropriate upper-level ontologies were taken into consideration to develop the highly standardized, incorporable, and industrial applicable models. Furthermore, the Ontopanel approach was utilized for mapping the real experimental data in the developed knowledge graphs and the resulting RDF files were successfully evaluated through the SPARQL queries. T2 - ICMMM 2023: 10th International Conference on Mechanics, Materials and Manufacturing CY - Washington, D.C., USA DA - 18.08.2023 KW - Ontology KW - Knowledge graph KW - Data mapping KW - Vickers hardness KW - FAIR data PY - 2023 AN - OPUS4-58100 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Ontology-Oriented Modeling of the Vickers Hardness Knowledge Graph T2 - Advances in Science and Technology N2 - This research deals with the development of the Vickers hardness knowledge graph, mapping the example dataset in them, and exporting the data-mapped knowledge graph as a machine-readable Resource Description Framework (RDF). Modeling the knowledge graph according to the standardized test procedure and using the appropriate upper-level ontologies were taken into consideration to develop the highly standardized, incorporable, and industrial applicable models. Furthermore, the Ontopanel approach was utilized for mapping the real experimental data in the developed knowledge graphs and the resulting RDF files were successfully evaluated through the SPARQL queries. KW - Data Mapping KW - FAIR Data KW - Ontology KW - Knowledge Graph KW - Vickers Hardness PY - 2024 DO - https://doi.org/10.4028/p-k8Gj2L VL - 149 SP - 33 EP - 38 PB - Trans Tech Publications Ltd CY - Switzerland AN - OPUS4-59981 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Digital representation of materials testing data for semantic web analytics: Tensile stress relaxation testing use case N2 - This study aims to represent an approach for transferring the materials testing datasets to the digital schema that meets the prerequisites of the semantic web. As a use case, the tensile stress relaxation testing method was evaluated and the testing datasets for several copper alloys were prepared. The tensile stress relaxation testing ontology (TSRTO) was modeled following the test standard requirements and by utilizing the appropriate upper-level ontologies. Eventually, mapping the testing datasets into the knowledge graph and converting the data-mapped graphs to the machine-readable Resource Description Framework (RDF) schema led to the preparation of the digital version of testing data which can be efficiently queried on the web. T2 - ICMDA 2024: 7th International Conference on Materials Design and Applications CY - Tokyo, Japan  DA - 09.04.2024 KW - Digitalization KW - Tensile stress relaxation KW - Ontology KW - Mechanical testing KW - Semantic web PY - 2024 AN - OPUS4-59979 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Bauer, Felix A1 - Uhlemann, Patrick A1 - Rehmer, Birgit A1 - Skrotzki, Birgit T1 - KupferDigital mechanical testing datasets: Stress relaxation and low-cycle fatigue (LCF) tests N2 - The KupferDigital project deals with the development of a data ecosystem for digital materials research on the basis of ontology-based digital representations of copper and copper alloys. This document provides exemplary mechanical testing datasets for training the developed KupferDigital infrastructures. Different types of cast copper alloys were provided for this research and their mechanical testing (stress relaxation and low-cycle fatigue) was performed in the accredited materials testing laboratory, while the test results were reported according to the DIN/ISO standards and attached with the maximum possible metadata about the sample history, equipment, and calibration. The attached content file consisted of the obtained primary raw testing data as well as the secondary datasets of these tests containing the detailed metadata of mechanical testing methods. Such test data files are processed by the KupferDigital digital tools to be converted to standardized machine-readable data files. KW - Copper alloys KW - Dataset KW - Stress relaxation KW - Mechanical testing KW - Low-cycle fatigue. PY - 2024 DO - https://doi.org/10.5281/zenodo.10820437 PB - Zenodo CY - Geneva AN - OPUS4-59665 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Bauer, Felix A1 - Tikana, Ladji A1 - Uhlemann, Patrick A1 - Thärig, Steffen A1 - Rehmer, Birgit A1 - Skrotzki, Birgit T1 - KupferDigital mechanical testing datasets N2 - The KupferDigital project aims to develop digital methods, tools, and data space infrastructures for digitalizing the entire life cycle of copper materials. The mechanical testing process is one of the main chains of such life cycles which generates lots of important testing data about the mechanical properties of the materials and their related materials and testing metadata. To train the digitalization of the mechanical testing process, different kinds of copper alloys were provided for this project, and their mechanical properties were measured by typical methods like Brinell and Vickers hardness and tensile testing. The primary raw testing data as well as the secondary datasets of these tests are provided. The detailed materials specifications, the utilized mechanical testing methods, and provided datasets are described in the content file. The test data files of heterogeneous structures are processed by the KupferDigital digital tools to be converted to standardized machine-readable data files. KW - Copper alloys KW - Dataset KW - Tensile testing KW - Mechanical testing KW - Hardness test PY - 2023 DO - https://doi.org/10.5281/zenodo.7670582 PB - Zenodo CY - Geneva AN - OPUS4-57038 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beygi Nasrabadi, Hossein A1 - Hanke, T. A1 - Eisenbart, M. A1 - Skrotzki, Birgit T1 - Materials Mechanical Testing Ontology (MTO) N2 - The materials mechanical testing ontology (MTO) was developed by collecting the mechanical testing vocabulary from ISO 23718 standard, as well as the standardized testing processes described for various mechanical testing of materials like tensile testing, Brinell hardness test, Vickers hardness test, stress relaxation test, and fatigue testing. Confirming the ISO/IEC 21838-2 standard, MTO utilizes the Basic Formal Ontology (BFO), Common Core Ontology (CCO), Industrial Ontologies Foundry (IOF), Quantities, Units, Dimensions, and data Types ontologies (QUDT), and Material Science and Engineering Ontology (MSEO) as the upper-level ontologies. Reusing these upper-level ontologies and materials testing standards not only makes MTO highly interoperable with other ontologies but also ensures its acceptance and applicability in the industry. MTO represents the mechanical testing entities in the 230 classes and four main parts: i) Mechanical testing experiments entities like tensile, hardness, creep, and fatigue tests as the subclasses of mseo:Experiment, ii) Mechanical testing quantity concepts such as toughness, elongation, and fatigue strength in the appropriate hierarchies of bfo:Disposition and bfo:Quality classes, iii) Mechanical testing artifacts like indenter as the subclasses of cco:Artifact, and iv) mechanical testing data like the stress-strain, S-N, or creep curves as the subclasses of cco:InformationContentEntity. MTO is publicly available via the KupferDigital GitLab repository. T2 - FEMS EUROMAT 2023 CY - Frankfurt a. M., Germany DA - 03.09.2023 KW - Mechanical testing KW - Ontology KW - Standard PY - 2023 AN - OPUS4-58270 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit A1 - Hanke, Thomas A1 - Eisenbart, Miriam T1 - Mechanical testing ontology N2 - The materials mechanical testing ontology (MTO) was developed by collecting the mechanical testing vocabulary from ISO 23718 standard, as well as the standardized testing processes described for various mechanical testing of materials like tensile testing, Brinell hardness test, Vickers hardness test, stress relaxation test, and fatigue testing. Confirming the ISO/IEC 21838-2 standard, MTO utilizes the Basic Formal Ontology (BFO), Common Core Ontology (CCO), Industrial Ontologies Foundry (IOF), Quantities, Units, Dimensions, and data Types ontologies (QUDT), and Material Science and Engineering Ontology (MSEO) as the upper-level ontologies. KW - Ontology KW - Mechanical testing KW - FAIR data PY - 2023 UR - http://industryportal.enit.fr/ontologies/MTO PB - National Center for Biomedical Ontology CY - Stanford AN - OPUS4-58271 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -