Ontologies for Models and Algorithms in Applied Mathematics and Related Disciplines
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arXiv
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| Autores principales: | , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| _version_ | 1866911972822351872 |
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| author | Schembera, Björn Wübbeling, Frank Kleikamp, Hendrik Biedinger, Christine Fiedler, Jochen Reidelbach, Marco Shehu, Aurela Schmidt, Burkhard Koprucki, Thomas Iglezakis, Dorothea Göddeke, Dominik |
| author_facet | Schembera, Björn Wübbeling, Frank Kleikamp, Hendrik Biedinger, Christine Fiedler, Jochen Reidelbach, Marco Shehu, Aurela Schmidt, Burkhard Koprucki, Thomas Iglezakis, Dorothea Göddeke, Dominik |
| contents | In applied mathematics and related disciplines, the modeling-simulation-optimization workflow is a prominent scheme, with mathematical models and numerical algorithms playing a crucial role. For these types of mathematical research data, the Mathematical Research Data Initiative has developed, merged and implemented ontologies and knowledge graphs. This contributes to making mathematical research data FAIR by introducing semantic technology and documenting the mathematical foundations accordingly. Using the concrete example of microfracture analysis of porous media, it is shown how the knowledge of the underlying mathematical model and the corresponding numerical algorithms for its solution can be represented by the ontologies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_20443 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Ontologies for Models and Algorithms in Applied Mathematics and Related Disciplines Schembera, Björn Wübbeling, Frank Kleikamp, Hendrik Biedinger, Christine Fiedler, Jochen Reidelbach, Marco Shehu, Aurela Schmidt, Burkhard Koprucki, Thomas Iglezakis, Dorothea Göddeke, Dominik Artificial Intelligence Databases Digital Libraries Information Retrieval H.3; H.4; I.2.4 In applied mathematics and related disciplines, the modeling-simulation-optimization workflow is a prominent scheme, with mathematical models and numerical algorithms playing a crucial role. For these types of mathematical research data, the Mathematical Research Data Initiative has developed, merged and implemented ontologies and knowledge graphs. This contributes to making mathematical research data FAIR by introducing semantic technology and documenting the mathematical foundations accordingly. Using the concrete example of microfracture analysis of porous media, it is shown how the knowledge of the underlying mathematical model and the corresponding numerical algorithms for its solution can be represented by the ontologies. |
| title | Ontologies for Models and Algorithms in Applied Mathematics and Related Disciplines |
| topic | Artificial Intelligence Databases Digital Libraries Information Retrieval H.3; H.4; I.2.4 |
| url | https://arxiv.org/abs/2310.20443 |