The Center for HelioAnalytics (CfHA) establishes a Community of Practice to envision solutions using machine learning, knowledge capture, and data analytics to expand the discovery potential for key heliophysics research topics and missions. Our primary goal is to build sustainable connections in the Heliophysics Community for the purpose of supporting efforts to harness data science, machine learning, and AI to drive scientific discovery. This is a leveraging effort: our team members are involved in multiple data science projects spanning a wide range of data sets and a diverse array of analysis techniques.
Data science and machine learning is already driving discovery physics. Piecemeal efforts within NASA’s Heliophysics Division have successfully employed sophiscated analysis to enhance specific science objectives in the past. Additionally, many efforts within our community are dedicated to providing services to the greater scientific community, including virtual observatories, data systems, browser interfaces and software development. The CfHA fills a critical gap within the field of heliophysics to combine these specialized areas of expertise in order to ensure that the full potential of analytical methods have maximal impact on the science. A committee or workshop cannot do this alone; only a dedicated infrastructure effort like the CfHA can grow the partnerships and resources that are vital to our community.
CfHA’s unique focus is on how heliophysics data sets and models result in scientific knowledge without partitioning efforts based on the mission or the environment in which they occur. We exploit commonalities in processing information via data and models in order to amplify scientific potential. In this light, the primary objectives are
We have several focus teams: each promotes the fulfillment of these primary objectives through basic research, deployment, mission development, and community building and development. Since our primary goal is a self-sustaining community of practice, we have partnered with several other organizations to promote a healthy data science community.
