Heliophysics Discovery Tools for the 21st Century: Data Science and Machine Learning Structures and Recommendations for 2020-2050
/ Authors
R. McGranaghan, B. Thompson, E. Camporeale, J. Bortnik, M. Bobra, G. Lapenta, S. Wing, B. Poduval, S. Lotz, S. Murray
and 7 more authors
M. Kirk, T. Y. Chen, H. Bain, P. Riley, B. Tremblay, M. Cheung, V. Delouille
/ Abstract
Three main points: 1. Data Science (DS) will be increasingly important to heliophysics; 2. Methods of heliophysics science discovery will continually evolve, requiring the use of learning technologies [e.g., machine learning (ML)] that are applied rigorously and that are capable of supporting discovery; and 3. To grow with the pace of data, technology, and workforce changes, heliophysics requires a new approach to the representation of knowledge.
Journal: ArXiv