Ontologies for Models and Algorithms in Applied Mathematics and Related Disciplines
This work addresses data management issues for researchers in applied mathematics, though it is incremental as it builds on existing semantic technology.
The paper tackles the challenge of making mathematical research data FAIR by developing ontologies and knowledge graphs for models and algorithms, demonstrating this with a microfracture analysis example.
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.