From Observation to Impacts: Provenance for Earth Science Resources

Wednesday, 17 December 2014: 4:30 PM
Hook Hua1, Curt Tilmes2, Peter Arthur Fox3, Stephan Zednik4, Brian Duggan5, Steve Aulenbach5, Brian D Wilson6, Gerald John Maramba Manipon7 and Ana Pinheiro Privette8, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)NASA Headquarters, Washington, DC, United States, (3)Rensselaer Polytechnic Inst., Troy, NY, United States, (4)Rensselaer Polytechnic Institute, Troy, NY, United States, (5)US Global Change Research Program, Washington D.C., DC, United States, (6)Jet Propulsion Laboratory, Pasadena, CA, United States, (7)Raytheon Company Pasadena, Pasadena, CA, United States, (8)Climate Data Solutions, LLC, Asheville, NC, United States
NASA’s Earth Science Data Systems Working Group (ESDSWG) on Provenance is working on a provenance specification for use in Earth science data systems to capture, consume, and interpret the end-to-end data life cycle information. Based on W3C PROV, this Earth Science extension can be used as an interoperable specification for representing Earth science resources that includes observations by instruments, data producers, data processing systems, data archive centers, data users, analysis findings, and societal impacts.

NASA is participating in the Big Earth Data Initiative (BEDI) and also leading a related Climate Data Initiative (CDI) effort. Under CDI, NASA is also working with the U.S. Global Change Research Program (USGCRP) and the U.S. Group on Earth Observations (USGEO) to identify and make interoperable relevant data from multiple interagency sources. These interagency efforts will improve the discoverability, accessibility, and usability of Federal data and information products derived from civil Earth observations.

We will present our progress to develop a provenance specification for representing Earth science resources from observation to impacts and how it can be used to support these initiatives. We will show how it can be used in earth science data systems to automatically capture, consume, and interpret provenance information using semantic technologies.