Small Data Analysis
Winter Semester 2023/24
The semester is organized within the framework of the Berlin Mathematics Research Center MATH+ and supported by the Einstein Foundation Berlin. We are committed to fostering an atmosphere of respect, collegiality, and sensitivity. Please read our MATH+ Collegiality Statement.
“Why there are only 40 golden statues (among thousands) in the Cachette of Karnack?” — This Thematic Einstein Semester will deal with the analysis of small complex data sets, a small number of research objects, or rare objects, for which standard statistical methods are not applicable and the data itself does not sufficiently represent expert knowledge. We propose a counter movement to the need for large training sets, but rather to revive classical mathematics (algebra, topology, logic, geometry,…) for the application of data analysis.
Small data sets are common when the events of interest are hard to observe such as certain diseases, meteorological phenomena, or (pre-)historic findings. The complexity of the examined objects allows for a large variety of analysis answers, the relevance of which cannot be justified by the sparse data itself. Even if the studied systems can be simulated, the relevant events might occur rarely leading to prohibitive sampling costs or uncertainty.
The Thematic Einstein Semester aims to intensify the collaboration between mathematicians and researchers from other disciplines who develop research methods for small data sets.
Accompanying Lecture Series
Depending on capacities also open for guests from all disciplines:
- Seminar on “Geometric Deep Learning”, FU Berlin, Wednesdays 14:15-15:45, A6/SR 025/026 (Arnimallee 6)
- Lecture on “Logische Datenanalyse” (within Mathematics II), October 24th 2023, 08:15-9:45, Lecture Hall B (B.004), Arnimallee 22
1st Workshop: An interdisciplinary workshop on knowledge-driven analytics
The first workshop of the Thematic Einstein Semester will be held from November 1 to 3 at the Zuse Institute Berlin. It is an opportunity to find future research topics and collaborations. It is the prelude to a Thematic Einstein Semester, which deals with the interaction of mathematics and non-mathematical disciplines. In our first workshop we deal with research questions and data from different disciplines and see how mathematics comes into play in interdisciplinary projects. Success stories but also critical views on this collaboration have their say. The following questions are examined in particular: Transition from the research question to the mathematical problem – is that possible? Can expert knowledge (beyond the concrete data) be represented mathematically? What is the impact of complexity reduction? Can mathematical structures be found in interdisciplinary research objects?
More details can be found on the workshop website and on the workshop flyer.
2nd Workshop: 17. – 19.01.2024
The second workshop of the Thematic Einstein Semester will be held from January 17 to 19, 2024, at Zuse Institute Berlin. This workshop mainly addresses mathematical questions concerning the use of data analysis methods for small data sets. It will present a broad range of mathematical fields and, thus, make methods more transparent to the users.
Registration form and program can be found here
Hackathon: 22. – 24.01.2024
A Hackathon of the Thematic Einstein Semester will be held from January 22 – 24. Different groups will be sat on computers and will ‘calculate’ and discuss specific case studies from different disciplines.
Final Conference: 11. – 12.03.2024
The Final Conference aims at the theme of “Interpretation of mathematical results”. For example: How does contextual knowledge come into play?
The results will be presented and summarized.
Podcasts
Throughout the Thematic Einstein Semseter, we will create a thematic Podcast that casts a spotlight on particular interfaces between real-world applications and mathematics, introducing them to a broader research community as well as the general public.
Examples of small data
Here we have cllected examples of small data from various projects.