Mathematical models are among the central research objects of mathematics and its applications. However, they are usually documented only indirectly: in publications, software repositories, datasets, or project-specific descriptions. Essential information – assumptions, defining equations, model variants, corresponding research problems, associated computational tasks, and implementations – is scattered across different sources and communities. This makes it often difficult to find existing models, compare related formulations, and reuse mathematical knowledge beyond the original publication context.

Within the Mathematical Research Data Initiative (MaRDI), the mathematics consortium of the German National Research Data Infrastructure (NFDI), the Mathematical Models Database (MathModDB) addresses this problem by treating mathematical models explicitly as structured research data. MathModDB represents models and their surrounding mathematical context in a knowledge graph, linking academic disciplines, research problems, formulations, quantities, computational tasks, and publications. Users can navigate from a research problem to suitable model classes, inspect and compare different formulations of a model, and identify related models across disciplines.

In this talk, we present the status of MathModDB and its integration into the MaRDI ecosystem. We describe the underlying ontology, the representation of mathematical knowledge in the graph, and the workflow for adding and reviewing model information. Since MathModDB is integrated in the MaRDI Portal, which builds on Wikibase technology, the community can contribute directly: models can be entered through guided questionnaires in MaRDMO – a MaRDI extension of the research data management planning tool RDMO – or edited via the portal's web interface, and contributions can be manually reviewed to maintain consistency with the underlying ontology.

We illustrate the approach with examples from applied mathematics, showing how models are connected to research problems, defining formulations, and related resources. We also touch upon ongoing work on linking MathModDB to executable model representations such as ModelingToolkit.jl, and on the long-term maintenance of mathematical knowledge beyond the current funding period, where relying on open standards and Wikibase technology keeps a migration path towards community-driven infrastructures open. A key challenge, finally, is community-driven curation: a knowledge graph of mathematical models can only thrive through contributions and review from the mathematical community itself – an effort for which MaRDI builds on its partnership with professional societies such as the DMV.