Computational provenance in hydrologic science: a snow mapping example

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Authors
Dozier, Jeff
Frew, James
Subjects
Snow
Remote sensing
Data management
Provenance
Advisors
Date of Issue
2008
Date
Publisher
Royal Society Publishing
Language
Abstract
Computational provenance—a record of the antecedents and processing history of digital information—is key to properly documenting computer-based scientific research. To support investigations in hydrologic science, we produce the daily fractional snow- covered area from NASA’s moderate-resolution imaging spectroradiometer (MODIS). From the MODIS reflectance data in seven wavelengths, we estimate the fraction of each 500 m pixel that snow covers. The daily products have data gaps and errors because of cloud cover and sensor viewing geometry, so we interpolate and smooth to produce our best estimate of the daily snow cover. To manage the data, we have developed the Earth System Science Server (ES3), a software environment for data-intensive Earth science, with unique capabilities for automatically and transparently capturing and managing the provenance of arbitrary computations. Transparent acquisition avoids the scientists having to express their computations in specific languages or schemas in order for provenance to be acquired and maintained. ES3 models provenance as relationships between processes and their input and output files. It is particularly suited to capturing the provenance of an evolving algorithm whose components span multiple languages and execution environments.
Type
Article
Description
The article of record as published may be found at http://dx.doi.org/10.1098/rsta.2008.0187
URI
https://hdl.handle.net/10945/52428
Series/Report No
Department
Organization
University of California, Santa Barbara
Donald Bren School of Environmental Science and Management
Identifiers
NPS Report Number
Sponsors
NASA
Funded by Naval Postgraduate School.
Funder
Cooperative Agreements NNG0C52A and NNG04GE66G (NASA)
N00244-07-1-0013 (NPS)
Format
Citation
J. Dozier, J. Frew, "Computational provenance in hydrologic science: a snow mapping example," Philosophical Transactions of the Royal Society A, v.367 (2009), pp. 1021-1033.
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