FAIRmath: Opening mathematical research data for the next generation

Findability, accessibility, interoperability, and reusability (FAIR) are the key principals for modern research data.
While data-driven science started to implement these principals for measurement and simulation data, it is not completely immanent how these principles translate to (pure) mathematics research. Although mathematics research results are time independent, a new generation of mathematicians demands a timely research infrastructure. In this symposium, we discuss the question of FAIR data for mathematics from two perspectives:
1) What are the needs of future mathematicians and
2) what is technically possible today?

Dienstag 24.9.
SR 2.066
10:00Michael KohlhaseMathematical Data wants to be Deep FAIR
10:24Fabian RackOpeness and FAIRness for mathematical research data: the legal framework
10:48Moritz SchubotzCollecting Datasets by Analyzing References in the zbMATH Database
11:12Wolfgang DalitzalsoMATH - A Database for Mathematical Algorithms and Software
11:36Christian HimpeCultivating Cooperation in a Competitive Community
SR 2.066
16:00Lars KastnerConfirmable workflows in polymake
16:24Claus FiekerStorage of Number Fields and Related Objects
16:48Thomas KopruckiModal Pathway Diagrams for the Representation of Mathematical Models
17:12Howard S. CohlFrom the A&S handbook to a digital mathematics platform: reusing the DLMF for the DRMF