The topology of data
Abstract
A wealth of complex data is increasingly available in almost every aspect of the physical and social world. Such copious data offer the potential to help unlock new ways of understanding and manipulating our surroundings. The demographic characteristics of human populations convey information about heterogeneous regions of a city or a country, and our online activities encode data about who we are and what we do. Networked systems—in people, cities, animals, plants, computers, and more—are also rich in data, which are present both in their structure and in their dynamics. The flows of nutrients in vascular structures, the complicated dynamics of fluids, and the forces in granular materials all provide huge amounts of complex data. Parsing—and hopefully eventually understanding—such data requires a diverse set of tools.
Additional Information
We thank Karen Daniels and Ryan Hurley for their comments on an early version of this manuscript. We also thank Christine Middleton and an anonymous reviewer for their many helpful suggestions. Michelle Feng thanks the James S. McDonnell Foundation for financial support. Eleni Katifori acknowledges partial support by NSF award PHY-1554887, the University of Pennsylvania Materials Research Science and Engineering Center through NSF award DMR-1720530, and the Simons Foundation through award 568888.Files
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Additional details
- Eprint ID
- 119177
- Resolver ID
- CaltechAUTHORS:20230209-988069100.11
- DOI
- 10.1063/PT.3.5157
- PHY-1554887
- NSF
- DMR-1720530
- NSF
- 568888
- Simons Foundation
- Created
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2023-03-15Created from EPrint's datestamp field
- Updated
-
2023-03-15Created from EPrint's last_modified field