Data Literacy
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About the Project data.RWTH
The data.RWTH project aims to enable students to acquire data literacy on a broad scale. To this end, courses are being developed at RWTH that train various aspects of data literacy. The Center for teaching and Learning Services is collaborating with various departments at the university, including lecturers from various faculties and the research data management team.
After three years of funding under the Data Literacy Education NRW program of the Digitale Hochschule NRW, the project has been continued by RWTH since May 2023.
More information about our courses and other project activities can be found on the following pages:
What is Data Literacy?
The competence to appropriately and critically collect and evaluate, manage, analyze and interpret data is indispensable in the 21st century. Hence, Data Literacy is one of several so-called Future Skills. In 2021, a number of institutions have committed themselves to the importance of data literacy in the Data Literacy Charta. In addition to the German government's Digital Council and the Stifterverband, RWTH has also signed the paper. According to the Data Literacy Charta, acting data literate means finding answers to the following questions when dealing with data:
- "What do I want to do with data? Data and data analysis are not an end in themselves, but serve a concrete application in the real world.
- What can I do with data? Data sources and their quality as well as the state of technical and methodological developments open up possibilities and set limits.
- What am I allowed to do with data? All legal rules of data use (for example, data protection, copyrights, and licensing issues) must always be considered.
- What should I do with data? Because data is a valuable resource, it derives a normative requirement to use it for the benefit of individuals and society."
Like other competencies, data literacy continues to develop with new technologies. In higher education, a competent approach to data therefore also includes appropriate programming languages and the ability to deal with artificial intelligence in a reflective manner. The latter is discussed as AI literacy in close connection with data literacy.