Strategies to introduce Data Management techniques into the German university curriculum

Data Management is high on the agenda of the German Research Organizations and Universities. While many organizations have committed to high level data management plans, these plans are often loosely binding and not followed adequately. As a consequence, few practical concepts are in place, implementing a sustainable reliable processing, archiving and publication of research data. While many institutions struggle with the organizational level, at which data management is implemented, Students are educated and time is lost, teaching them relevance, techniques and strategies in dealing in a thoughtful and ahead looking manner with their research data. Within a new research project we are tackling this problem in a two-fold way. 1. we are involving technical university personnel, who are working in labs, producing scientific data, in data management processes. This requires teaching, analysis of lab practices and the development of applications for support. 2. We are developing new teaching material, in order to introduce such DM strategies into regular practical courses conducted in such labs, by starting small scale experiments on long term time series. These can be analyzed by student within practical courses, and will demonstrate the practical use of DM practices in the courses. While the focus is on natural science labs, we also strive to create material for other disciplines using e.g. text analysis techniques, in particular in linguistics and history. By doing so, we are touching not only the traditional data-heavy disciplines, but try to bridge responsibility for this task over several disciplines and faculties, in order to raise broad acceptance and recognition in the whole university for the benefits of structured Data Management plans in projects.