References
- Arp, R., Smith, B. and Spear, A.D. (2015) Building ontologies with Basic Formal Ontology. Cambridge, MA: Massachusetts Institute of Technology. Available at: 10.7551/mitpress/9780262527811.001.0001
- Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M. and Sherlock, G. (2000) ‘Gene Ontology: Tool for the unification of biology’, Nature Genetics, 25, pp. 25–29. Available at: 10.1038/75556
- Bayerlein, B., Schilling, M., Birkholz, H., Jung, M., Waitelonis, J., Mädler, L. and Sack, H. (2024) ‘PMD Core Ontology: Achieving semantic interoperability in materials science’, Materials & Design, 237, p. 112603. Available at: 10.1016/j.matdes.2023.112603
- Benjamin, P., Patki, M. and Mayer, R. (2006) ‘Using ontologies for simulation modeling’, Proceedings of the 2006 Winter Simulation Conference. Monterey, CA, USA,
3–6 December . Piscataway, NJ:IEEE , pp. 1151–1159. Available at: 10.1109/WSC.2006.323206 - Brandt, N., Griem, L., Herrmann, C., Schoof, E., Tosato, G., Zhao, Y., Zschumme, P. and Selzer, M. (2021) ‘Kadi4Mat: A research data infrastructure for materials science’, Data Science Journal, 20, p. 8. Available at: 10.5334/dsj-2021-008 Website:
https://kadi.iam.kit.edu/ (Accessed: 1 August 2025). - CEN Workshop (2018)
Materials modelling – Terminology, classification and metadata. CWA 17284:2018 . Brussels: CEN. - Cheong, H. and Butscher, A. (2019) ‘Physics-based simulation ontology: An ontology to support modelling and reuse of data for physics-based simulation’, Journal of Engineering Design, 30, pp. 655–687. Available at: 10.1080/09544828.2019.1644301
- De Baas, A., Nostro, P.D., Friis, J., Ghedini, E., Goldbeck, G., Paponetti, I.M., Pozzi, A., Sarkar, A., Yang, L., Zaccarini, F.A. and Toti, D. (2023) ‘Review and alignment of domain-level ontologies for materials science’, IEEE Access, 11, pp. 120372–120401. Available at: 10.1109/ACCESS.2023.3327725
- Dublin Core Metadata Initiative (2019) DCMI: DCMI metadata terms. Available at:
https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ (Accessed: 1 January 2024). - Dumontier, M., Baker, C.J., Baran, J., Callahan, A., Chepelev, L., Cruz-Toledo, J., Del Rio, N.R., Duck, G., Furlong, L.I., Keath, N., Klassen, D., McCusker, J.P., Queralt-Rosinach, N., Samwald, M., Villanueva-Rosales, N., Wilkinson, M.D. and Hoehndorf, R. (2014) ‘The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery’, Journal of Biomedical Semantics, 5, p. 14. Available at: 10.1186/2041-1480-5-14
- Fathalla, S., Vahdati, S., Auer, S. and Lange, C. (2018) ‘SemSur: A core ontology for the semantic representation of research findings’, Procedia Computer Science, 137, pp. 151–162. Available at: 10.1016/j.procs.2018.09.015
- Frické, M. (2019) ‘The knowledge pyramid: The DIKW hierarchy’, Knowledge Organization, 46(1), pp. 33–46. Available at: 10.5771/0943-7444-2019-1-33
- Garijo, D. (2017) ‘WIDOCO: A wizard for documenting ontologies’, International Semantic Web Conference. Cham:
Springer , pp. 94–102. Available at: 10.1007/978-3-319-68204-4_9 - Ghedini, E., Goldbeck, G., Friis, J., Hashibon, A. and Schmitz, G. (2020). European Materials Modelling Ontology. Version 0.9.9. European Materials Modelling Council (EMMC). Available at:
emmo-repo.github.io/versions/0.9.9/emmo.pdf - Grolinger, K., Capretz, M.A.M., Marti, J.R. and Srivastava, K.D. (2012) Ontology–based representation of simulation models. London, Ontario, Canada: The University of Western Ontario (Electrical and Computer Engineering Publications, 30). Available at:
https://ir.lib.uwo.ca/electricalpub/30 . - Gruber, T.R. (1995) ‘Toward principles for the design of ontologies used for knowledge sharing’, International Journal of Human-Computer Studies, 43(5–6), pp. 907–928. Available at: 10.1006/ijhc.1995.1081
- Himanen, L., Geurts, A., Foster, A.S. and Rinke, P. (2019) ‘Data-driven materials science: Status, challenges, and perspectives’, Advanced Science (Weinheim), 6(21), p. 1900808. Available at: 10.1002/advs.201900808
- Horsch, M.T., Toti, D., Chiacchiera, S., Seaton, M.A., Goldbeck, G. and Todorov, I.T. (2021) OSMO: Ontology for Simulation, Modelling, and Optimization. Zenodo. Available at: 10.5281/zenodo.5084394 (Accessed: 01 April 2025).
- Iglezakis, D., Terzijska, D., Arndt, S., Leimer, S., Hickmann, J., Fuhrmans, M. and Lanza, G. (2023) ‘Modelling scientific processes with the m4i ontology’, 1st Conference on Research Data Infrastructure (coRDI) – Connecting Communities, 2023. Karlsruhe, Germany,
12–14 September .TIB Open Publishing , pp. 1–5., 1. Available at: 10.52825/cordi.v1i.271 - Information Technology—Top-Level Ontologies (TLO)—Part 1: Requirements, Standard ISO/IEC 21838-1:2021 (2021) Available at:
https://www.iso.org/obp/ui/en/#iso:std:iso-iec:21838:-1:ed-1:v1:en (Accessed: 31 December 2024). - Jones, D., Bench-Capon, T. and Visser, P. (1998)
‘Methodologies for ontology development’ , IT&KNOWS - Information Technology and Knowledge Systems, 15th IFIP World Computer Congress. Vienna, Austria, and Budapest, Hungary. - kadi-APY documentation (2025) Available at:
https://kadi-apy.readthedocs.io/en/stable/ (Accessed: 15 April 2025). - Keestra, M. (2017) ‘Metacognition and reflection by interdisciplinary experts: Insights from cognitive science and philosophy’, Issues in Interdisciplinary Studies, 35, pp. 121–169.
http://interdisciplinarystudies.org/docs/Vol35_2017/08_121-169.pdf - Konchakova, N., Klein, P., Lidorikis, E., Laskarakis, A., Cavalcanti, W.L. and Friis, J. (2022) Position paper: Open innovation in horizon Europe. Available at: 10.5281/ZENODO.5848551 (Accessed: 15 April 2025).
- Lacy, L. and Gerber, W. (2004) ‘Potential modeling and simulation applications of the Web Ontology Language - OWL’, Proceedings of the 2004 Winter Simulation Conference, 2004. Washington, D.C.,
5–8 December . Piscataway, NJ:IEEE , pp. 257–262. Available at: 10.1109/WSC.2004.1371325 (Accessed: 15 September 2025). - Lebo, T., Sahoo, S.S., McGuinness, D.L., Belhajjame, K., Cheney, J., Corsar, D., Garijo, D., Soiland-Reyes, S., Zednik and S., Zhao, J. (2013) PROV-O: The PROV Ontology. W3C Recommendation, 30 April 2013. Cambridge, MA: World Wide Web Consortium (W3C). Available at:
https://www.w3.org/TR/prov-o/ - Matentzoglu, N., Malone, J., Mungall, C. and Stevens, R. (2018) ‘MIRO: Guidelines for minimum information for the reporting of an ontology’, Journal of Biomedical Semantics, 9, p. 6. Available at: 10.1186/s13326-017-0172-7
- May, M.C., Kiefer, L., Kuhnle, A. and Lanza, G. (2022) ‘Ontology-based production simulation with OntologySim’, Applied Sciences, 12, p. 1608. Available at: 10.3390/app12031608
- Musen, M.A. (2015) ‘The Protégé project: A look back and a look forward’, AI Matters. Association of Computing Machinery Specific Interest Group in Artificial Intelligence, 1(4). Available at: 10.1145/2757001.2757003
- Noman, H.M. (2023) Onto-MS: An ontology for multiscale simulation methods. Available at:
https://kit-mms.github.io/Onto-MS.github.io/ (Accessed: 1 June 2024). - Noman, H.M. (2024)
‘Script for converting Ontology to an ELN (i.e., Kadi4Mat) ‘ . (Version 2.0). Available at Zenodo. 10.5281/zenodo.13921378 - Noy, N.F. and McGuinness, D.L. (2001) Ontology development 101: A guide to creating your first ontology. Stanford, CA: Stanford University, Knowledge Systems Laboratory.
- O’Connor, M.J. and Das, A.K. (2009) ‘SQWRL: A query language for OWL’, in R. Hoekstra and P.F. Patel-Schneider (eds.) Proceedings of OWL: Experiences and directions (OWLED), fifth international workshop (OWLED 2009), Chantilly, VA,
23–24 October 2009 . CEUR Workshop Proceedings, Vol. 529. Aachen:CEUR-WS , pp. 1–8.Available at:https://ceur-ws.org/Vol-529/owled2009_submission_42.pdf - Pinto, H.S. and Martins, J.P. (2004) ‘Ontologies: How can they be built?’, Knowledge and Information Systems, 6, pp. 441–464. Available at: 10.1007/s10115-003-0138-1
- POLiS – Cluster of Excellence (2019) POLiS – cluster of excellence. Available at:
https://www.postlithiumstorage.org/en (Accessed: 12 May 2025). - Project Management Institute (ed.) (2021) The standard for project management and a guide to the project management body of knowledge (PMBOK guide). Seventh edition. Newtown Square, PA: Project Management Institute, Inc.
- Prud’hommeaux, E. and Seaborne, A. (2008) SPARQL query language for RDF. W3C recommendation, 15 January 2008. Available at:
https://www.w3.org/TR/rdf-sparql-query/ (Accessed: 30 May 2025). - RDFLib documentation (2025) RDFLib: A Python library for working with RDF. Available at:
https://rdflib.readthedocs.io/en/stable/ (Accessed: 15 August 2025). - Rubin, D.L., Grossman, D., Neal, M., Cook, D.L., Bassingthwaighte, J.B. and Musen, M.A. (2006) ‘Ontology-based representation of simulation models of physiology’, AMIA Annual Symposium Proceedings 2006. Washington, D.C.,
11–15 November .American Medical Informatics Association (AMIA) , pp. 664–668. - Schema.org (2019) Home - schema.org. Available at:
https://schema.org/ (Accessed: 1 January 2025). - Schmitt, R.H., Anthofer, V., Auer, S., Başkaya, S., Bischof, C. and Bronger, T. (2020) NFDI4Ing - the National Research Data Infrastructure for Engineering Sciences. Available at: 10.5281/ZENODO.4015201 (Accessed: 15 June 2025).
- Silver, G.A., Miller, J.A., Hybinette, M., Baramidze, G. and York, W.S. (2011) ‘DeMO: An ontology for discrete-event modeling and simulation’, SIMULATION, 87, pp. 747–773. Available at: 10.1177/0037549710386843
- TIB, Leibniz (2022) TIB terminology service. Available at:
https://terminology.tib.eu/ (Accessed: 1 June 2025). - Turnitsa, C., Padilla, J.J. and Tolk, A. (2010) ‘Ontology for modeling and simulation’, Proceedings of the 2010 Winter Simulation Conference. Baltimore, MD,
5–8 December . Piscataway, NJ:IEEE , pp. 643–651. Available at: 10.1109/WSC.2010.5679124 - Yao, L., Divoli, A., Mayzus, I., Evans, J.A. and Rzhetsky, A. (2011) ‘Benchmarking ontologies: Bigger or better?’, PLoS Computational Biology, 7, p.
e1001055 . Available at: 10.1371/journal.pcbi.1001055
