As part of our “Trainings” work package, the DKZ.2R plans to curate and provide a variety of trainings, seminars and courses. We will start by offering an official The Carpentries Workshop on the 21st and 22nd of November 2024 on the topic of “plotting and programming in Python”. The Carpentries Workshop by DKZ.2R: Python basics and plotting The workshop will be hosted on-site at RWTH Aachen University and is open for up to 25 participants. The workshop material is available online and will be presented by official carpentry instructors who will walk you through the steps and are available for questions the whole time. The course is teaching the very basics of Python and although some experience with other scripting/programming languages is beneficial, no prior knowledge is required for the course. Furthermore, the event is open for participants from all domains. If you are interested in taking part in the workshop you can sign up here.

Related Posts

How To: Good Scientific Practice

How To: Good Scientific Practice

“Scientific integrity forms the basis for trustworthy research”, so it says in the Guidelines for Safeguarding Good Research Practice of the DFG, the German Research Foundation. As a major funder of research in Germany the DFG, as well as many other funders of research in Germany and the European Union, requires researchers to follow a certain set of rules conducting their research. These rules are called “good scientific practice” and have to be followed by researchers to be viable for funding. According to the guidelines researchers are required to “document all information relevant to the production of a research result as clearly as is required by and is appropriate for the relevant subject area to allow the result to be reviewed and assessed”. But good scientific practice is not done by documenting your research. It also includes i.a. protecting the personality rights of your subjects and handling research data in an appropriate manner by e.g. “back(-ing) up research data and results made publicly available, as well as the central materials on which they are based and the research software used, by adequate means according to the standards of the relevant subject area, and retain them for an appropriate period of time.” This is where Research Data Management (RDM) comes in. Of course RDM is much more than just creating a backup of your data on a USB-Stick and handing it over to anyone asking for it. “Good scientific practice” in RDM follows the FAIR principles:

Read More
Documentation From User Experience

Documentation From User Experience

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.

Read More
Call for participation

Call for participation

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!

Read More