Thu - Fri 27 Mar 2025 - 28 Mar 2025Past

By DKZ.2R: Data Competence College

Event Aachen (IT Center)

The first Data Competence College will be hosted from March 26th to 28th at the IT center of RWTH Aachen. Based on the concept of the Wissenschaftskolleg in Berlin or the Institute of Advanced Studies in Princeton, we have invited four individuals with high data competence from different scientific fields (“Data Experts”) as part of the data competence college.

As of now, Prof. Sebastian Houben from Hochschule Bonn-Rhein-Sieg (specialist in AI and autonomous systems), and Dr. Moritz Wolter from University of Bonn (expert in high performance computing and machine learning) have already confirmed their participation.

For three days we aim to create a space where local scientists, and especially early career researchers, can learn from the data experts and each other regarding research data and methods but also data experts can inspire each other. The schedule includes keynote presentations by all data experts, poster presentations by the participants, and 1:1 sessions between data experts and early career researchers, as well as a variety of method- and data-related workshops. We aim at creating an environment in which everyone feels safe to give input, share their knowledge and learn from the other participants and experts.

The exchange with and among experts from different disciplines and/or areas of focus in particular can provide new impetus for data processing or methodical data analysis. In this way, the DKZ.2R Data Competence College forms the focus of mutual enrichment participants and experts alike.

Event Details:

  • Time: Thursday, March 27th @ 9am - Friday, March 28th @ 1pm, 2025
  • Location: Kopernikusstraße 6, 52074 Aachen, Seminarraum 003 (Directions via OpenStreetMaps, Google Maps)

Schedule of Events: PDF Version | SVG Version | Plain Text

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
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
Do's and Don'ts in Research Data Management

Do's and Don'ts in Research Data Management

Research Data Management Do’s and Don’ts - Step up your RDM skills!

1. Structuring and naming your folders There is an easy way to make your data findable for you and your team: establish a folder structure which makes sense for you and your working group as well as naming conventions for your folders.

Don’t:

Paul and Suzie
»Guideline
>application
»version2_final
»v.3
»review
»3rd.version
>JD
»qn
»0-1

Instead do:

000_int_orga
»01_application
»02_review 120_questionaires
»01_qualitative »02_quantitative 130_data
»01_qualitative »02_quantitative

Read More