There is a growing interest in learning data topology, from theoretical results to real-world applications. Topological learning is an emerging field which is expected to bring new insights in all the areas of the data mining and knowledge discovery process. More and more people approach the field of topological learning from different and interesting angles. They come from various communities such as data mining, statistics, geometry, topology, physics, medicine or engineering. We believe that now is the right time to establish and enhance communication between these communities.
This workshop aims to gather researchers to bring new ideas, discuss their experience and contribute to the theoretical and practical maturation of topological learning. It will address issues related to the concepts of learning data topology within the data mining and knowledge discovery process, which implies to work on every step, starting from the preprocessing (e.g. structuring and organizing) to the visualization and interpretation of the results, via the data mining methods themselves.