IN23C-1736
An Analysis of Earth Science Data Analytics Use Cases

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Chung-Lin Shie, NASA/GSFC, Greenbelt, MD, United States and Steven J Kempler, NASA Goddard Space Flight Center, Greenbelt, MD, United States
Abstract:
The increase in the number and volume, and sources, of globally available Earth science data measurements and datasets have afforded Earth scientists and applications researchers unprecedented opportunities to study our Earth in ever more sophisticated ways. In fact, the NASA Earth Observing System Data Information System (EOSDIS) archives have doubled from 2007 to 2014, to 9.1 PB (Ramapriyan, 2009; and https://earthdata.nasa.gov/about/system-performance). In addition, other US agency, international programs, field experiments, ground stations, and citizen scientists provide a plethora of additional sources for studying Earth. Co-analyzing huge amounts of heterogeneous data to glean out unobvious information is a daunting task.

Earth science data analytics (ESDA) is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. It can include Data Preparation, Data Reduction, and Data Analysis. Through work associated with the Earth Science Information Partners (ESIP) Federation, a collection of Earth science data analytics use cases have been collected and analyzed for the purpose of extracting the types of Earth science data analytics employed, and requirements for data analytics tools and techniques yet to be implemented, based on use case needs. ESIP generated use case template, ESDA use cases, use case types, and preliminary use case analysis (this is a work in progress) will be presented.