English

From Theory to Practice: Demonstrators of FAIR Data Spaces Across Different Sectors

Distributed, Parallel, and Cluster Computing 2024-12-09 v1

Abstract

The principles of data spaces for sovereign data exchange across trusted organizations have so far mainly been adopted in business-to-business settings, and recently scaled to cloud environments. Meanwhile, research organizations have established distributed research data infrastructures, respecting the principle that data must be FAIR, i.e., findable, accessible, interoperable and reusable. For mutual benefit of these two communities, the FAIR Data Spaces project aims to connect them towards the vision of a common, cloud-based data space for industry and research. Thus, the project establishes a common legal and ethical framework, common technical building blocks, and it demonstrates the orchestration of multiple building blocks in self-contained settings addressing a diverse range of use cases in domains including health, biodiversity, and engineering. This paper gives a summary of all demonstrators, ranging from research data infrastructures scaled to industry-ready cloud environments to work in progress on building bridges between operational business-to-business data spaces and research data infrastructures.

Keywords

Cite

@article{arxiv.2412.04969,
  title  = {From Theory to Practice: Demonstrators of FAIR Data Spaces Across Different Sectors},
  author = {Nikolaus Glombiewski and Zeyd Boukhers and Christian Beilschmidt and Johannes Drönner and Michael Mattig and Artur Piet and Robert Pietrzynski and Mehrshad Jaberansary and Macedo Maia and Sebastian Beyvers and Yeliz Üçer Yediel and Muhammad Hamza Akhtar and Heiner Oberkampf and Jonathan Hartman and Bernhard Seeger and Christoph Lange},
  journal= {arXiv preprint arXiv:2412.04969},
  year   = {2024}
}

Comments

Accepted at the 40th ACM/SIGAPP Symposium On Applied Computing