Abstract
AbstractIn 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.
Funder
Bundesanstalt für Materialforschung und -Prüfung
Fraunhofer Group Materials and Components
Bundesministerium für Bildung und Forschung
Bundesanstalt für Materialforschung und -prüfung (BAM)
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,General Materials Science
Reference15 articles.
1. Ghiringhelli LM, Carbogno C, Levchenko S et al (2017) Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats. Npj Comput Mater 3:46. https://doi.org/10.1038/s41524-017-0048-5
2. Wilkinson MD, Dumontier M, Aalbersberg IJ et al (2016) The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3:160018. https://doi.org/10.1038/sdata.2016.18
3. Cheung K (2008) Towards an ontology for data-driven discovery of new materials. In: Semantic scientific knowledge integration AAAI/SSS workshop. The Association for the Advancement of Artificial Intelligence (AAAI), Stanford University, Palo Alto, CA, p 6
4. Ashino T (2010) Materials ontology: an infrastructure for exchanging materials information and knowledge. Data Sci J 9:54–61. https://doi.org/10.2481/dsj.008-041
5. Glick J (2013) Ontologies and databases—knowledge engineering for materials informatics. Informatics for materials science and engineering. Elsevier, Amsterdam, pp 147–187
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