MathHub Data is a unified infrastructure to support FAIR mathematical research data. Specifically, it aims to support the usual kind of data -- data that conform to the relational data model, in contrast to, for example, formalised mathematics or research papers. MathHub Data builds on and is a part of the MathHub portal for narrative and symbolic mathematical data. The datasets are available as virtual theories. These abstract from the storage level and are well-integrated with mathematical documents and knowledge on MathHub.
The infrastructure provided by MathHub Data includes storage and a searchable interface for datasets. The team is setting up a dataset submission process that will involve peer review, and thus improve the reliability of published data.
- Dataset authors can specify the meaning of mathematical objects and their database encoding via MDDL schema theories, based on mathematical background knowledge already on MathHub,
- Users can interact with data set objects as with any other objects on MathHub via the MathHub front-end, tools, and APIs.
The MathHub Data setup ensures
- long-term availability of the data
- user interfaces, APIs, and interoperability at the database level and the mathematical level
- license and provenance management.