Ontopanel: A Tool for Domain Experts Facilitating Visual Ontology Development and Mapping for FAIR Data Sharing in Materials Testing
Source abstract
Abstract
Abstract 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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Research Data Management Practices · Scientific Computing and Data Management · Semantic Web and Ontologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (15)
Show source-provided references
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/s41524-017-0048-510.1038/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.2016.1810.1038/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.008-04110.2481/dsj.008-041 ↗
5. Glick J (2013) Ontologies and databases—knowledge engineering for materials informatics. Informatics for materials science and engineering. Elsevier, Amsterdam, pp 147–18710.1016/B978-0-12-394399-6.00008-4 ↗
6. Bayerlein B, Hanke T, Muth T et al (2022) A perspective on digital knowledge representation in materials science and engineering. Adv Eng Mater. https://doi.org/10.1002/adem.20210117610.1002/adem.202101176 ↗
7. Na HS, Choi OH, Lim JE (2006) A method for building domain ontologies based on the transformation of UML models. In: Fourth international conference on software engineering research, management and applications (SERA’06). IEEE, Seattle, WA, USA, pp 332–338
8. Mejhed Mkhinini M, Labbani-Narsis O, Nicolle C (2020) Combining UML and ontology: an exploratory survey. Comput Sci Rev 35:100223. https://doi.org/10.1016/j.cosrev.2019.10022310.1016/j.cosrev.2019.100223 ↗
9. Liepinš R, Grasmanis M, Bojars U (2014) OWLGrEd ontology visualizer. In: Proceedings of the 2014 international conference on developers, pp 37–42
10. Shimizu C, Hammar K (2019) CoModIDE—the comprehensive modular ontology engineering IDE. In: ISWC 2019 satellite tracks. CEUR-WS, p 5
11. Dudas M, Hanzal T, Svatek V, Zamazal O (2015) OBOWLMorph: starting ontology development from PURO background models. In: 12th international experiences and directions workshop on OWL (OWLED), pp 14–20. Springer International Publishing Ag, Bethlehem10.1007/978-3-319-33245-1_2 ↗
12. Hanzal T, Svatek V, Vacura M (2016) Event categories on the semantic web and their relationship/object distinction. In: 9th international conference on formal ontology in information systems (FOIS), pp 183–196. Ios Press, Annecy, France
13. CWA 17815:2021 E (2021) Materials characterization—terminology, metadata and classification, European Committee for Standardization (CEN-CENELEC), Brussels, Belgium
14. Chávez-Feria S, García-Castro R, Poveda-Villalón M (2021) Converting UML-based ontology conceptualizations to OWL with chowlk. In: Verborgh R, Dimou A, Hogan A et al (eds) The semantic web: ESWC 2021 satellite events. Springer International Publishing, Cham, pp 44–4810.1007/978-3-030-80418-3_8 ↗
15. ISO 6506-1:2014-10 (2014) Metallic materials—Brinell hardness test—Part 1: Test method, International Organization for Standardization (ISO), Geneva, Switzerland