Towards Serverless Data Exchange Within Federations

Boris Sedlak, Victor Casamayor-Pujol, Praveen Kumar Donta, Sebastian Werner, Karl Wolf, Matteo Falconi, Frank Pallas, Schahram Dustdar, Stefan Tai, Pierluigi Plebani

Abstract: In this paper, we propose a novel approach for sharing privacy-sensitive data across federations of independent organizations, taking particular regard to flexibility and efficiency. Our approach benefits from data meshes and serverless computing – such as flexible ad-hoc composability or minimal operational overheads – to streamline data sharing phases, and to effectively and flexibly address the specific requirements of highly variable data sharing constellations.