Abstract
Global climate researchers rely upon many forms of sensor data and analytical methods to help profile subtle changes in climate conditions. The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) program provides researchers with a collection of curated Value Added Products (VAPs) resulting from continuous sensor data streams, data fusion, and modeling. We are leveraging the Open Provenance Model as a foundational construct that serves the needs of both the VAP producers and consumers. We are organizing the provenance in different tiers of granularity to model VAP lineage, causality at the component level within a VAP, and the causality for each time step as samples are being assembled within the VAP. This paper shares our implementation strategy and how the ARM operations staff and the climate research community can greatly benefit from this approach to more effectively assess and quantify VAP provenance.
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Stephan, E.G., Halter, T.D., Ermold, B.D. (2010). Leveraging the Open Provenance Model as a Multi-tier Model for Global Climate Research. In: McGuinness, D.L., Michaelis, J.R., Moreau, L. (eds) Provenance and Annotation of Data and Processes. IPAW 2010. Lecture Notes in Computer Science, vol 6378. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17819-1_5
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DOI: https://doi.org/10.1007/978-3-642-17819-1_5
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