From March 12th to 13th, 2026, SmallData will draw together all members of our CRC to share insights, collaborate, and delve into addressing the challenges of small data for meaningful discoveries!

In this seminar, our SmallData Associated Researchers will give a 30 minute presentation of their work on small data and explore how it connects with other projects across the Collaborative Research Center. Each seminar will feature an open Q&A session. A talk title and short description will be available closer to the time.

Title TBD
Heinz Wiendl (SmallData Associated Researcher)
Department of Neurology and Neurophysiology, Medical Center – University of Freiburg

In this seminar, our SmallData Associated Researchers will give a 30 minute presentation of their work on small data and explore how it connects with other projects across the Collaborative Research Center. Each seminar will feature an open Q&A session. A talk title and short description will be available closer to the time.

Title TBD
Janis Nolde (SmallData Associated Researcher)
Department of Nephrology, Medical Center – University of Freiburg

The Science Days take place every autumn – they are Germany’s largest science and STEM festival.

Together with institutions from the fields of science, education and business, a fascinating and very diverse programme is put together. STEM topics are presented from different directions and perspectives, and visitors get insights into highly topical issues and their research. Hands-on activities play a very important role here. Visitors are encouraged to try things out, experiment and tinker! In exchange with the actors and under their expert guidance, visitors can gain new insights and expand their knowledge. Another highlight of the programme are our spectacular science shows, which guarantee aha and wow experiences.

SmallData will be participating this year! Please come and visit our stand!

In this seminar, our SmallData Associated Researchers will give a 30 minute presentation of their work on small data and explore how it connects with other projects across the Collaborative Research Center. Each seminar will feature an open Q&A session. A talk title and short description will be available closer to the time.

Title TBD
Maria Kalweit (SmallData Associated Researcher)
Department of Computer Science, Faculty of Engineering, University of Freiburg

The SmallData team, with the support of ‘Women in Data Science Worldwide’ (WiDS)*, aim to bring together all SmallData female career advanced and early career researchers for fostering connections across career levels. In a still rather male-dominated leadership world, this retreat will provide a space to exchange experiences, discuss challenges, and explore opportunities for female leadership.

* WiDS @ SmallData is independently organized by CRC 1597 ‘Small Data’ to be part of the mission to increase participation of women in data science and to feature outstanding women doing outstanding work.

This workshop discusses different application settings and concepts of synthetic data in a small data context. We will focus on data types such as temporal and longitudinal data, data with a hierarchical structure, and disease gene prioritization. In addition to discussing whether synthetic data underestimates uncertainty and how to use synthetic experts to assess the quality of generated data, we will demonstrate the models and tools currently in use to generate these data types.

Moderator: Clemens Schächter (A03)

Large language models (LLM) can deal with information which for long time has been thought to only be processable by humans with a given contextual knowledge. Being neural networks, LLMs learn to quantify context sensitive similarity of textual information, also referred to as attention. Specifically by employing this similarity mechanism on multiple layers of abstraction, LLMs allow to address a certain level of a lack in structure and heterogeneity, e.g., in writing style and employed nomenclature, because similarity can be computed on the level of the semantics.

Still, a lack of structure and heterogeneity poses problems when small amounts of information are hidden in a large text, i.e., a low signal to noise ratio, which is the case for scientific literature on rare diseases or when a large heterogeneity is observed such as in doctors’ reports.

In this workshop we want to identify/develop specific use cases which represent the above described challenges from SmallData and develop approaches which (1) address the challenges and (2) quantify the uncertainty of the extracted information.

We give clinical researchers the opportunity to present their challenge of extracting information from heterogeneous text sources. These can be scientific publications such case reports or doctors’ reports describing the state of individual patients.

Participants from biomedicine describe the data, the specific problem and indicate the hurdles with respect to data protection. In addition they also indicate a panel of experts which is willing to validate the results retrieved from the LLMs.

Participants from computer science and statistical data science then infer feasible solutions for the challenge and develop a methodological research question that is in line with the SmallData objectives.

Goal of the workshop is to establish availability of datasets, specific biomedical use cases and strategies for validation of extracted information.

Moderator: Fabian Kabus (F)

In this seminar, our SmallData Associated Researchers will give a 30 minute presentation of their work on small data and explore how it connects with other projects across the Collaborative Research Center. Each seminar will feature an open Q&A session. A talk title and short description will be available closer to the time.

Title TBD
Jana Naue (SmallData Associated Researcher)
Institute of Forensic Medicine, Medical Center – University of Freiburg

A joint Workshop of CRC 1597 Small Data, the STRATOS initiative, EVA4MII and PrivateAIM

This two-day workshop focuses on designing synthetic benchmark datasets, complemented by diagnostic tools, tailored to the challenges commonly encountered in clinical cohort data, with an emphasis on small data scenarios. These challenges — often present in clinical routine data — are insufficiently addressed by existing methods when there is a combination of multiple problems, leaving a gap in methodological development. Please find more information, including program and registration, on the dedicated webpage.