TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Vickers test ontology (VTO) N2 - Vickers Test Ontology (VTO) has developed for representing the Vickers testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6507-1 standard. Versions info: V2 developed using BFO+CCO top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/process-graphs/vickers-hardness-test GitHub: https://github.com/HosseinBeygiNasrabadi/Vickers-Test-Ontology-VTO- MatPortal: https://matportal.org/ontologies/VTO IndustryPortal: https://industryportal.enit.fr/ontologies/VTO KW - Ontology KW - Knowledge graph KW - Data mapping KW - Vickers hardness KW - FAIR data. PY - 2024 UR - https://gitlab.com/kupferdigital/process-graphs/vickers-hardness-test UR - https://github.com/HosseinBeygiNasrabadi/Vickers-Test-Ontology-VTO- UR - https://matportal.org/ontologies/VTO UR - https://industryportal.enit.fr/ontologies/VTO PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-60544 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - Towards interoperability: Digital representation of a material specific characterization method N2 - Certain metallic materials gain better mechanical properties through controlled heat treatments. In age-hardenable aluminum alloys, the strengthening mechanism is based on the controlled formation of nanometer sized precipitates, which hinder dislocation movement. Analysis of the microstructure and especially the precipitates by transmission electron microscopy allows identification of precipitate types and orientations. Dark-field imaging is often used to image the precipitates and quantify their relevant dimensions. The present work aims at the digital representation of this material-specific characterization method. Instead of a time-consuming, manual image analysis, a digital approach is demonstrated. The integration of an exemplary digital workflow for quantitative precipitation analysis into a data pipeline concept is presented. Here ontologies enable linking of contextual information to the resulting output data in a triplestore. Publishing digital workflow and ontologies ensures the reproducibility of the data. The semantic structure enables data sharing and reuse for other applications and purposes, demonstrating interoperability. T2 - TMS - 7th World Congress on Integrated Computational Materials Engineering (ICME) CY - Orlando, Florida, USA DA - 21.05.2023 KW - Ontology KW - Semantic Interoperability KW - Digtial Representation KW - Data Management KW - Reproducibility KW - FAIR PY - 2023 AN - OPUS4-57548 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - Towards Interoperability: Digital Representation of a Material Specific Characterization Method N2 - Certain metallic materials gain better mechanical properties through controlled heat treatments. For example, in age-hardenable aluminum alloys, the strengthening mechanism is based on the controlled formation of nanometer sized precipitates, which represent obstacles to dislocation movement. Precise tuning of the material structure is critical for optimal mechanical behavior in the application. Therefore, analysis of the microstructure and especially the precipitates is essential to determine the ideal parameters for the interplay of material and heat treatment. Transmission electron microscopy (TEM) is utilized to identify precipitate types and orientations in a first step. Dark-field imaging (DF-TEM) is often used to image the precipitates and to quantify their relevant dimensions. The present work aims at the digital representation of this material-specific characterization method. Instead of a time-consuming, manual image analysis, an automatable, digital approach is demonstrated. Based on DF-TEM images of different precipitation states of a wrought aluminum alloy, a modularizable digital workflow for quantitative precipitation analysis is presented. The integration of this workflow into a data pipeline concept will also be discussed. Thus, by using ontologies, the raw image data, their respective contextual information, and the resulting output data from the quantitative precipitation analysis can be linked in a triplestore. Publishing the digital workflow and the ontologies will ensure the reproducibility of the data. In addition, the semantic structure enables data sharing and reuse for other applications and purposes, demonstrating interoperability. The presented work is part of two digitization initiatives, the Platform MaterialDigital (PMD, materialdigital.de) and Materials-open-Laboratory (Mat-o-Lab). T2 - MSE 2022 CY - Darmstadt, Germany DA - 27.09.2022 KW - Interoperability KW - Ontology KW - Precipitation Analysis PY - 2022 AN - OPUS4-55892 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Towards digitalization of materials in PMD: An application ontology of the tensile test N2 - Due to the diversity of materials and the processes associated with their production and use, the complexity of the lifecycles of materials and the multitude of academic and industrial researchers participating in generation of data for material design impose a huge challenge. The topical goal of digitalizing materials and processes can only be adequately addressed by consolidating the efforts of all stakeholders in this field. There are many scattered activities, but there is a demand for an elimination of redundancies as well as an advance in acceptance and a common basis in the digitalization of materials. Furthermore, data analysis methods play an important role in both, the experimental and simulation-based digital description of materials, but they have been poorly structured so far. Therefore, the two joint projects Platform Material Digital (PMD, materialdigital.de) and Materials open Laboratory (Mat-o-Lab, matolab.de) aim to contribute to a standardized description of data processing methods in materials research. Besides stimulating the formation of a collaborative community in this respect, their main technical goals are the quality assurance of the processes and the output data, the acquisition and definition of their accuracy as well as the interoperability between applications. In this regard, data management in accordance with the FAIR (findability, accessibility, interoperability, reuseability) principles is addressed. There is a common agreement in the scientific community following current discussions that data is supposed to be conform to these principles. This includes storage, processing and querying of data in a preferably standardized form. To meet the challenge to contextualize material data in a way that is consistent with all stakeholders, all necessary information on the condition of the material including production and application-related changes have to be made available via a uniform, machine-readable description. For this purpose, ontologies are to be used since they allow for machine-understandable knowledge representations and conceptualizations that are needed for data management and the digitalization in the field of materials science. As first efforts in PMD and Mat-o-Lab, application ontologies are created to explicitly describe processes and test methods. Thereby, the well-known tensile test of metals at room temperature was described ontologically in accordance with the respective ISO standard 6892-1:2019-11. The efforts in creating this tensile test application ontology are shown in this presentation. Especially, the path of ontology development based on standards to be pursued is focused, which is in accordance with the generic recommendations for ontology development and which is supposed to be exemplary for the creation of other application ontologies. T2 - VirtMet: 1st International Workshop on Metrology for Virtual Measuring Instruments and Digital Twins CY - Online meeting DA - 21.09.2021 KW - Platform Material Digital (PMD) KW - Ontology KW - Tensile test KW - Standard KW - Ontology development PY - 2021 AN - OPUS4-53481 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Portella, P. T1 - The contribution of the Platform MaterialDigital (PMD) in building up a Materials Data Space - Application to glass design and manufacturing N2 - Suitable material solutions are of key importance in designing and producing components for engineering systems – either for functional or structural applications. Materials data are generated, transferred, and introduced at each step along the complete life cycle of a component. A reliable materials data space is therefore crucial in the digital transformation of an industrial branch. A great challenge in establishing a materials data space lies in the complexity and diversity of materials science and engineering. It must be able to handle data from different knowledge areas over several magnitudes of length scale. The Platform MaterialDigital (PMD) is expected to network a large number of repositories of materials data, allowing the direct contact of different stakeholders as materials producers, testing labs, designers and end users. Following the FAIR principles, it will promote the semantic interoperability across the frontiers of materials classes. In the frame of a large joint initiative, PMD works intensively together with currently near 20 research consortia in promoting this exchange (www.material-digital.de). In this presentation we will describe the status of our Platform MaterialDigital. We will also present in more detail the activities of GlasDigital, one of the joint projects mentioned above dealing with the digitalization of glass design and manufacturing. (https://www.bam.de/Content/EN/Projects/GlasDigital/glasdigital.html) T2 - OntoCommons Workshop CY - Berlin, Germany DA - 04.04.2023 KW - Ontology KW - Materials Data Space KW - PMD KW - Glass PY - 2023 AN - OPUS4-60371 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Portella, Pedro Dolabella T1 - The contribution of the Platform MaterialDigital (PMD) in building up a Materials Data Space - Application to glass design and manufacturing N2 - Suitable material solutions are of key importance in designing and producing components for engineering systems – either for functional or structural applications. Materials data are generated, transferred, and introduced at each step along the complete life cycle of a component. A reliable materials data space is therefore crucial in the digital transformation of an industrial branch. A great challenge in establishing a materials data space lies in the complexity and diversity of materials science and engineering. It must be able to handle data from different knowledge areas over several magnitudes of length scale. The Platform MaterialDigital (PMD) is expected to network a large number of repositories of materials data, allowing the direct contact of different stakeholders as materials producers, testing labs, designers and end users. Following the FAIR principles, it will promote the semantic interoperability across the frontiers of materials classes. In the frame of a large joint initiative, PMD works intensively together with currently near 20 research consortia in promoting this exchange (www.material-digital.de). In this presentation we will describe the status of our Platform MaterialDigital. We will also present in more detail the activities of GlasDigital, one of the joint projects mentioned above dealing with the digitalization of glass design and manufacturing. (https://www.bam.de/Content/EN/Projects/GlasDigital/glasdigital.html) T2 - Onto Commons Workshop CY - Berlin, Germany DA - 04.04.2023 KW - Ontology KW - Data space PY - 2023 AN - OPUS4-58732 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Tensile Test: From Standard to PMD Application Ontology N2 - Data analysis methods play an important role in both the experimental and simulation-based digital description of materials but have so far been poorly structured. The platform Material Digital (PMD) should contribute to a standardized description of data processing methods in materials research. The goal is the quality assurance of the processes and the output data, the acquisition and definition of their accuracy as well as the interoperability between applications. Therefore, application ontologies are created to explicitly describe processes and test methods. In this presentation, the first efforts in creating a tensile test application ontology in accordance with the ISO standard 6892-1:2019-11 are shown. Especially, the path of ontology development to be pursued based on standards was focused. T2 - Onboarding Workshop der Plattform Material Digital (PMD) CY - Online meeting DA - 13.04.2021 KW - Ontology KW - Platform MaterialDigital KW - PMD KW - Tensile Test KW - Normung KW - Standardization PY - 2021 AN - OPUS4-52425 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus T1 - Tensile Test Ontology used in Platform Material Digital (PMD) N2 - Data analysis methods play an important role in both the experimental and simulation-based digital description of materials but have so far been poorly structured. The platform Material Digital (PMD) is supposed to contribute to a standardized description of data processing methods in materials research. The goal is the quality assurance of the processes and the output data, the acquisition and definition of their accuracy as well as the interoperability between applications. Therefore, application ontologies are created to explicitly describe processes and test methods. In this presentation, the first efforts within the joint project PMD in creating a tensile test application ontology in accordance with the ISO standard 6892-1:2019-11 are shown. Especially, the path of ontology development to be pursued based on standards was focused. Furthermore, the presentation includes a live demonstration of queries possibly performed to query data that was uploaded in the PMD triple store. T2 - Online Workshop: An introduction to the semantic web and ontologies CY - Online meeting DA - 23.04.2021 KW - Ontology KW - Tensile Test KW - Platform Material Digital KW - PMD KW - Knowledge Graphs KW - Semantic Web PY - 2021 AN - OPUS4-52949 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Schilling, Markus T1 - Tensile Test Ontology (TTO) N2 - This is the stable version 2.0.1 of the PMD ontology module of the tensile test (Tensile Test Ontology - TTO) as developed on the basis of the 2019 standard ISO 6892-1: Metallic materials - Tensile Testing - Part 1: Method of test at room temperature. The TTO was developed in the frame of the PMD project. The TTO provides conceptualizations valid for the description of tensile test and corresponding data in accordance with the respective standard. By using TTO for storing tensile test data, all data will be well structured and based on a common vocabulary agreed on by an expert group (generation of FAIR data) which will lead to enhanced data interoperability. This comprises several data categories such as primary data, secondary data and metadata. Data will be human and machine readable. The usage of TTO facilitates data retrieval and downstream usage. Due to a close connection to the mid-level PMD core ontology (PMDco), the interoperability of tensile test data is enhanced and data querying in combination with other aspects and data within the broad field of material science and engineering (MSE) is facilitated. The TTO class structure forms a comprehensible and semantic layer for unified storage of data generated in a tensile test including the possibility to record data from analysis, re-evaluation and re-use. Furthermore, extensive metadata allows to assess data quality and reproduce experiments. Following the open world assumption, object properties are deliberately low restrictive and sparse. KW - Ontology KW - Tensile Test KW - Digitalization KW - Plattform MaterialDigital KW - Structured Data PY - 2023 UR - https://github.com/MarkusSchilling/application-ontologies/blob/479311832819af695a2c64fa8eb772f2da398061/tensile_test_ontology_TTO/pmd_tto.ttl UR - https://github.com/materialdigital/core-ontology/blob/59f5727b0437ceea5e3d9fcb8fcd0ac211e92cc3/pmd_tto.ttl PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-57935 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Beygi Nasrabadi, Hossein A1 - Skrotzki, Birgit T1 - Tensile test ontology (TTO) N2 - Tensile Test Ontology (TTO) has developed for representing the Tensile testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6892-1 standard. Versions info: V2 developed using BFO+CCO top-level ontologies. V3 developed using PROVO+PMDco top-level ontologies. Repositories: GitLab: https://gitlab.com/kupferdigital/process-graphs/tensile-test GitHub: https://github.com/HosseinBeygiNasrabadi/Tensile-Test-Ontology-TTO- MatPortal: https://matportal.org/ontologies/TTO IndustryPortal: https://industryportal.enit.fr/ontologies/TTO KW - Ontology KW - Tensile testing PY - 2024 UR - https://gitlab.com/kupferdigital/process-graphs/tensile-test UR - https://github.com/HosseinBeygiNasrabadi/Tensile-Test-Ontology-TTO- UR - https://matportal.org/ontologies/TTO UR - https://industryportal.enit.fr/ontologies/TTO PB - GitLab CY - San Francisco, CA, USA AN - OPUS4-60545 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -