%0 Journal Article
%A Kern, Jori
%A Brechtel, Markus
%A Kaluza, Philipp
%A Kussel, Tobias
%A Vehreschild, Jörg Janne
%A Lablans, Martin
%T Data Science Orchestrator: A Containerized Trusted Research Environment for Flexible and Secure Analytical Pipelines.
%J Studies in health technology and informatics
%V 15
%@ 0926-9630
%C Amsterdam
%I IOS Press
%M DKFZ-2025-01005
%P 698-702
%D 2025
%Z #EA:E260#LA:E260#
%X Without dedicated research and processing environments, researchers sometimes tend to use software downloaded from the internet on non-versioned data sets, making reproduction of the results very difficult while risking leaks of the sensitive data, by running it on their regular laptops. This also makes the process of analysis rather tedious and slow. The Data Science Orchestrator (DSO) aims to provide a easy solution to deploy different analysis tools in a turnkey solution making research safe and reproducible. By analyzing the requirements of researchers across our community we also identified a number of research infrastructure needs beyond this initial data analysis stage; therefore the scope of the DSO has expanded to provide federated analysis of data and repeated reporting using automated analysis pipelines that can be run at different intervals, hence extending its assistive impact beyond initial analysis.
%K Software
%K Computer Security
%K Data Science: methods
%K Humans
%K Data Processing (Other)
%K Software Development (Other)
%K Trusted Research Environment (Other)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:40380547
%R DOI:10.3233/SHTI250438
%U https://inrepo02.dkfz.de/record/301367