SIGDIUS Seminar - online - 2pm

June 14, 2023, 2:00 p.m. (CEST)

Time: June 14, 2023, 2:00 p.m. (CEST)
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Unifying research data: strategies for managing domain-specific metadata, schemas, and repositories

The Special Interest Group Data Infrastructure offers a forum to interested working groups that want to set up or further develop an RDM infrastructure at working group or institute level. We invite you to a monthly SIGDIUS seminar, to which we invite internal and external experts for presentations and discussions. SIGDIUS members will have the opportunity to exchange their experiences with concrete RDM infrastructures.

We cordially invite all interested parties to our next meeting on 14 June 2023 at 2 pm. This seminar will be held as an online seminar. For participation, please send an e-mail to Juergen.Pleiss@itb.uni-stuttgart.de.

Patrick Diehl
(JOSS)
JOSS and FLOSS for science: Examples for promoting open source software and science communication

Simon Hauser, Max Hausch
(IPVS / University of Stuttgart)
Improving reproducibility of scientific software using Nix/NixOS

Ensuring the reproducibility of scientific software is crucial for the advancement of research and the validation of scientific findings. However, achieving reproducibility in software-intensive scientific projects is often challenging due to dependencies, system configurations, and software environments. In this talk, we present a solution for these challenges by utilizing Nix and NixOS. Nix is a package manager and functional language that allows to mitigate these problems by guaranteeing that a package and all its dependencies can be built reproducibly as long as there is a build plan at the desired time, while NixOS is a purely functional Linux distribution, built on top of Nix that enables the build of reproducible systems, not just packages and their dependencies. We present a case study on improving the reproducibility of preCICE, an open-source coupling library, and its available adapters using Nix and NixOS, by demonstrating how to create a reproducible and self-contained environment for preCICE and highlight the benefits of using Nix and NixOS for managing software and system configurations, resulting in improved reproducibility. In addition, we compare the performance and usability of Nix with two widely used high-performance computing solutions, Spack and EasyBuild. This evaluation enables us to assess the advantages and disadvantages of employing Nix to improve reproducibility in scientific software development within an HPC context.

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