Tool-based Support for the FAIR Principles for Control Theoretic Results: The "Automatic Control Knowledge Repository"

Abstract

In 2016 a collection of guiding principles for the management of scientific data was proposed by a consortium of scientists and organizations under the acronym FAIR (Findability, Accessibility, Interoperability, Reusability). As many other disciplines, control theory also is affected by the (mostly unintended) disregard of these principles and to some degree also suffers from a reproducibility crisis. The specific situation for that discipline, however, is more related to software, than to classical numerical data. In particular, since computational methods like simulation, numeric approximation or computer algebra play an important role, the reproducibility of results relies on implementation details, which are typically out of scope for written papers.While some publications do reference the source code of the respective software, this is by far not standard in industry and academia. Additionally, having access to the source code does not imply reproducibility due to dependency issues w. r. t. hardware and software components. This paper proposes a tool based approach consisting of four components to mitigate the problem: a) an open repository with a suitable data structure to publish formal problem specifications and problem solutions (each represented as source code) along with descriptive metadata, b) a web service that automatically checks the solution methods against the problem specifications and auxiliary software for local testing, c) a computational ontology which allows for semantic tagging and sophisticated querying the entities in the repo and d) a peer-oriented process scheme to organize both the contribution process to that repository and formal quality assurance.