Abstract
In this article, we analyze the state of research data in mathematics. We find that while the mathematical community embraces the notion of open data, the FAIR principles are not yet sufficiently realized. Indeed, we claim that the case of mathematical data is special, since the objects of interest are abstract (all properties can be known) and complex (they have a rich inner structure that must be represented). We present a novel classification of mathematical data and derive an extended set of FAIR requirements, which accomodate the special needs of math datasets. We summarize these as deep FAIR. Finally, we show a prototypical system infrastructure, which can realize deep FAIRness for one category (tabular data) of mathematical datasets.
Funding source: Deutsche Forschungsgemeinschaft
Award Identifier / Grant number: RA-18723-1 OAF
Funding source: Horizon 2020 Framework Programme
Award Identifier / Grant number: 676541
Funding statement: The authors were supported by DFG grant RA-18723-1 OAF and European Commission grant Horizon 2020 ERI 676541 OpenDreamKit. Most of the implementation of the current MathDataHub prototype is due to Tom Wiesing.
About the authors
Dr. Katja Berčič is a postdoc in the research group for Knowledge Representation/Processing (Computer Science) at FAU Erlangen-Nürnberg. While working on her PhD in mathematics (combinatorics) she became interested in how to improve the way mathematicians work with data. She followed this interest during a postdoc at the National Autonomous University of Mexico. Her research interests lie in the areas of knowledge representation and management, particularly for mathematics.
Prof. Dr. Michael Kohlhase is professor for Knowledge Representation/Processing (Computer Science) at FAU Erlangen-Nürnberg and adjunct associate professor for Computer Science at Carnegie Mellon University. His research interests include knowledge representation for STEM (science, technology, engineering, mathematics), inference-based techniques for natural language processing, computer-supported education, and user assistance. He pursues these (interrelated) topics focusing on the aspects of modular foundations (usually logical methods) and large-scale structures in document corpora. He has pursued these interests during extended visits to Carnegie Mellon University, SRI International, and the Universities of Amsterdam, Edinburgh, and Auckland.
PD Dr. Florian Rabe is a senior researcher at the Universities of Erlangen-Nürnberg. His research interests include logics, type systems, and programming languages for computer science and mathematics as well as knowledge representation, scalable implementation, and system interoperability for them. He is the creator and main author of the MMT language and system.
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