The hallmarks of Heliophysics are variability, complexity, and a continuously evolving data landscape, characterized by the four V’s of big data (i.e., Volume, Variety, Veracity, and Velocity). With the advent of the field of data science, referring to advanced data processing methods across the full data lifecycle (i.e., collection, management, storage, analysis, and visualization), we have new opportunities for deeper fundamental discovery of Heliophysics variability and complexity that cannot be fully addressed by traditional methods, and a more effective utilization of the available, forthcoming, and even unforeseen data.

However, developing data science solutions is a significant challenge, and one shared by virtually all disciplines, at different institutions, and across the public and private sectors, and progress requires new collaboration. The objectives of this working group will be to:

· Understand the data science advances occurring across disciplines, at different institutions, and in the public and private sectors; and

· Coordinate and align data science efforts occurring across disciplines to guide Heliophysics data science development and to promote interdisciplinary collaboration.

To accomplish these objectives, we will target the following activities and corresponding deliverables (non-exhaustive):

· To coordinate with groups across e.g., Earth Science, Astrophysics, and Planetary Science to understand the latest developments for data science in the sciences

o Deliverable: Identify new research vistas and funding avenues; Produce documentation capturing latest trends in data science for scientific discovery; Create new collaborations that are more capable of implementing data science solutions

· To identify, facilitate, and accomplish data science knowledge/methodology transfer across disciplines

o Deliverable: Hold interdisciplinary telecons to gather information; Represent the Heliophysics community across data science-focused projects and discussions; Produce resources (white papers, reviews, and general online resources) detailing successful use cases for methodology transfer

Founding working group members: Ryan McGranaghan (ASTRA, LLC) and Asti Bhat (SRI International)