Raising Awareness for Data FAIRness. An Approach to Developing FAIR Data Literacy in Engineering Sciences Undergraduate Courses

This talk models the FAIR data principles into teaching scenarios as a contribution to data literacy for undergraduate students. An ideal vehicle are database training sessions offered by course instructors or library staff to undergraduates because such courses have long been helping students develop information literacy. This skill of critically reflecting on information-seeking behavior and the use of information to create new knowledge can be expanded and adapted to introduce students to FAIR-compliant research data management. By working with databases in a supervised environment, students learn to interact with structured collections of data and to manage and process their results for later reuse. The FAIR Principles are particularly useful for distinguishing well-curated and standards-compliant data collections from websites without a clear curation policy