This special issue will show-case work which takes concepts or tools from the rich fields of topology, algebra, and geometry and brings them to bear on data science problems. Mathematicians working in topology, algebra, and geometry have more than a hundred years’ worth of finely-developed machinery whose purpose is to give structure to, help build intuition about, and generally better understand data and spaces beyond those that we can easily visualize. We expect the developed approaches to address a specific challenge and demonstrate utility on at least one interesting dataset. Submitted works should provide novel methodology and insight into interesting real-world datasets but are not required to be evaluated on conventional benchmarking datasets if these do not adequately capture the challenge which the paper seeks to address.

More information available at: www.springer.com/journal/44007/updates/19962244