Dagstuhl-Seminar — Applied and Combinatorial Topology

The last twenty years of rapid development of Topological Data Analysis (TDA) have shown the need of understanding the shape of data to better understand the data. Since an explosion of new ideas in 2000’ including those of Persistent Homology and Mapper Algorithms, the community rushed to solve detailed theoretical questions related to the existing invariants. However, topology and geometry have still much to offer to the data science community. New tools and techniques are within reach, waiting to be brought over the fence to enrich our understanding and potential to analyze data.