Description
The increasing digitalization and datafication of society have made data competencies essential for all citizens, not just for specialists in computer science or data science. As data-driven decision-making becomes central to business, government, and everyday life, the ability to critically engage with data is emerging as a key qualification for the 21st century. Especially in light of recent advances in artificial intelligence (AI) and machine learning (ML), understanding how data is generated, collected, and used has become more important than ever. Thus, universities have to prepare students from all study programmes for critically interact with data, may it be in the context of their future research, jobs or in their private lives.
In this context, the concept of Data Literacy—commonly defined as the ability to read, work with, analyze, and communicate with data—has gained significant traction in education. However, it is often narrowly understood as a set of technical or methodological skills, such as statistics or programming. As a result, Data Literacy is frequently perceived as "Data Science for beginners." In this presentation, we challenge that view and argue that Data Literacy represents a broader, interdisciplinary set of competencies that extend beyond the traditional scope of Data Science.
We will explore three key dimensions:
i) how Data Literacy empowers students from all disciplines to critically engage with data and foundational data science concepts;
ii) how it expands and enriches the scope of Data Science, making it relevant for students in computer science and related fields; and
iii) how Data Literacy initiatives can act as bridges between disciplines, fostering interdisciplinary collaboration and shared understanding.
In this context we will present current initiatives for the implementation of Data Literacy at the Friedrich Schiller University Jena. We will also discuss potential future developments and strategies for further embedding Data Literacy across the university.