Researchers in all empirical sciences produce and deal with increasingly larger and more complex data sets. Modern digital technologies enable the collection, manipulation, combination, and interpretation of data products for various research applications on ever-expanding scales. The challenges encountered when dealing with such data are shared across the research community. While solutions in many cases are custom-built, driven by, and tailored toward explicit scientific questions, the fundamental questions of how to manage research data, how to maximize its scientific value, and how to enable reuse for data mining and reinterpretation concern everybody.
This workshop will bring together researchers from across the TRAs who produce and deal with large and complex data sets and generate digital research products. We wish to stimulate an exchange of ideas and common challenges.
The workshop has three goals:
- Get an overview of the ongoing activities
- Identify common strengths, challenges, and development directions
- Provide feedback to the university on future requirements for an excellent digital infrastructure
As an outcome of the workshop, we foresee a whitepaper on requirements for modern research data management and data science infrastructures, which can inform the university's strategic planning in this area.