Data mining for science of the sun-earth connection as a single system - Alzate, Nathalia; Di Matteo, Simone; Morgan, Huw; Seaton, Daniel B.; Miralles, Mari Paz; Balmaceda, Laura; Kirk, Michael S.; West, Matthew; DeForest, Craig; Vourlidas, Angelos (Frontiers in Astronomy and Space Sciences, 2023)
Establishing the Sun-Earth connection requires overcoming the challenges of exploring the data from past and current missions and leveraging tools and models (data mining) to create an efficient system treatment of the Sun and heliosphere. However, solar and heliospheric environment data constitute a vast source of information whose potential is far from being optimally exploited. In the next decade, the solar and heliospheric community will have to manage the increasing amount of information coming from new missions, improve re-analysis of data from past and current missions, and create new data products from the application of new methodologies. This complex task is further complicated by practical challenges such as different datasets and catalogs in different formats that may require different pre-processing and analysis tools, and the need for numerous analysis approaches that are not all fully optimized for large volumes of data. While several ongoing efforts aim at addressing these problems, the available datasets and tools are not always used to their full potential often due to lack of awareness of available resources. In this paper, we summarize the issues raised and goals discussed by members of the community during recent conference sessions focused on data mining for science.