For this year’s Research Data Day (Tag der Forschungsdaten) NRW, on the 12th of November 2024, Forschungszentrum Jülich and the RWTH Aachen University teamed up again to host an on-site event, this time in Jülich, which will be co-organised by DKZ.2R. Similarly to the last years, there will be online talks in the morning which will be viewed publicly. After Lunch we are starting with the on-site program including different talks and theme tables. More information on the concept an the event can be found under this link.

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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

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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:

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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!

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