The primary goal of the Advancing Collaborative Connections for Earth System Science (ACCESS) Program is to adopt and implement technologies to effectively manage, discover and use NASA’s archive of Earth observations for scientific research and applications. This program complements NASA's Earth Observing System Data and Information System (EOSDIS) by engaging researchers and software developers external to EOSDIS in NASA's mission to "drive advances in science, technology, aeronautics, space exploration, economic vitality, and stewardship of the Earth" and furthers the Earth Science Strategic objective from the NASA 2014 Science Plan to "advance knowledge of Earth as a system to meet the challenges of environmental change and to improve life on our planet" (http://science.nasa.gov/about-us/sciencestrategy/). ACCESS aims to improve and expand the use of NASA's Earth science data by leveraging modern techniques for discovering, managing and analyzing large and complex Earth science data sets.
The primary focus of this program element is to help address data management, discoverability, and utilization challenges faced by users and curators of NASA’s Earth science data. Although focused on information technology implementation and deployment, the ACCESS program is targeted at addressing existing and anticipated future needs of the research and applied science communities. One of those needs is in the area of machine learning (ML). However, adoption of ML techniques relies heavily on availability of high-quality large training datasets. Thus, in addition to technology implementation, this program element seeks ways to create new training datasets for ML. Proposal teams must include both information technology and Earth science expertise and must be tied directly to and demonstrate specific issues facing Earth science and applied science users interacting with NASA's Earth science data.
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