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Mon Nov 18 2024 - Fri Nov 22 Past

Mon - Fri 18 Nov 2024 - 22 Nov 2024Past

By DKZ.2R: The Carpentries Workshop: Introduction to the Unix Shell, Git, and GitLab

Workshop Aachen (RWTH Aachen University)

Workshop Unix Shell Git GitLab Carpentries

The DKZ.2R presents, as a part of our “Trainings” work package, a Carpentries Workshop on the 18th and 22nd of November on the topic of “Introduction to the Unix Shell, Git, and GitLab”. This is an official Carpentries Workshop and will be hosted on-site at RWTH Aachen University.

Workshop material is available online and will be presented by official Carpentries instructors, who will guide you through the concepts with the help of hands-on exercises and personalized support. The course is designed for beginners and is open to participants from all domains. No prior knowledge is required. If you are interested in taking part in the workshop, you can sign up here.

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Documentation From User Experience

Marvin Lorber
Documentation , Software , RDM

This post is a condensed version of a talk at our Data Compentcy College

If you regularly use scientific software written by others, or tried to replicate interesting research that relies on software, you have probably also invested weeks of work to solve a software problem or even given up on a software because of missing documentation. Finding a project that might be the solution to your problem and then failing to run the code is frustrating. Being unable to run a project you have built yourself years ago is even worse. Having experienced all those setbacks myself in the past I want to use this post to channel that frustration to fuel solutions for better documentation for our current and future projects.

Call for participation

A. Janz
Consulting , Data , RDM , HPC , Data Science , Artificial Intelligence , Machine Learning

Call for participation!

The Data Literacy Center Rhine-Ruhr (DKZ.2R) issues a call for participation in its “rent-an-expert” project! We offer support for ambitious research projects of PhD students and early postdocs dealing with Data Science and Artificial Intelligence, High Performance Computing and Simulation, and Research Data Management. As the DKZ.2R is funded by the German Federal Ministry of Education and Research (BMBF) as well as the EU, this offer is free of charge!

How To: Open Science

A. Mielke
Data , RDM , Open Science

Tired of Recreating someone else’s work? - How Open Science can accelerate research and overcome reinvention

Have you ever found papers on algorithms but their implementation is missing? Found an interesting analysis but there is no way to check the results, as you don’t have access to the data they were derived from? Ever thought you had a great idea for a project, just to find out a year later that you are not the only research group following that specific idea? Not having access to other people’s code, data, metrics or even their plans for research projects often leads to unnecessary delays and scientific redundancies. There is an easy solution to overcome (almost) all of these issues. It’s called Open Science! What is Open Science? The UNESCO defines Open Science as a construct of “movements and practices aiming to make multilingual scientific knowledge openly available, accessible and reusable for everyone, to increase scientific collaborations and sharing of information for the benefits of science and society, and to open the processes of scientific knowledge creation, evaluation and communication to societal actors […]”. To ensure that everyone has access to scientific knowledge and infrastructure, Open Science focuses on four main concepts.