Heliophysics Discovery Tools for the 21st Century: Data Science and Machine Learning Structures and Recommendations for 2020-2050
This is an incremental recommendation for the heliophysics domain to improve data handling and discovery methods.
The paper addresses the need for heliophysics to adapt to growing data and technological changes by emphasizing the importance of data science and machine learning, recommending new knowledge representation approaches for 2020-2050.
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.