TY - GEN
T1 - Designing a provenance-based climate data analysis application
AU - Santos, Emanuele
AU - Koop, David
AU - Maxwell, Thomas
AU - Doutriaux, Charles
AU - Ellqvist, Tommy
AU - Potter, Gerald
AU - Freire, Juliana
AU - Williams, Dean
AU - Silva, Cláudio T.
PY - 2012
Y1 - 2012
N2 - Climate scientists have made substantial progress in understanding Earth's climate system, particularly at global and continental scales. Climate research is now focused on understanding climate changes over wider ranges of time and space scales. These efforts are generating ultra-scale data sets at very high spatial resolution. An insightful analysis in climate science depends on using software tools to discover, access, manipulate, and visualize the data sets of interest. These data exploration tasks can be complex and time-consuming, and they frequently involve many resources from both the modeling and observational climate communities. Because of the complexity of the explorations, provenance is critical, allowing scientists to ensure reproducibility, revisit existing computational pipelines, and more easily share analyses and results. In addition, as the results of this work can impact policy, having provenance available is important for decision-making. In this paper we describe, UV-CDAT, a workflow-based, provenance-enabled system that integrates climate data analysis libraries and visualization tools in an end-to-end application, making it easier for scientists to integrate and use a wide array of tools.
AB - Climate scientists have made substantial progress in understanding Earth's climate system, particularly at global and continental scales. Climate research is now focused on understanding climate changes over wider ranges of time and space scales. These efforts are generating ultra-scale data sets at very high spatial resolution. An insightful analysis in climate science depends on using software tools to discover, access, manipulate, and visualize the data sets of interest. These data exploration tasks can be complex and time-consuming, and they frequently involve many resources from both the modeling and observational climate communities. Because of the complexity of the explorations, provenance is critical, allowing scientists to ensure reproducibility, revisit existing computational pipelines, and more easily share analyses and results. In addition, as the results of this work can impact policy, having provenance available is important for decision-making. In this paper we describe, UV-CDAT, a workflow-based, provenance-enabled system that integrates climate data analysis libraries and visualization tools in an end-to-end application, making it easier for scientists to integrate and use a wide array of tools.
UR - http://www.scopus.com/inward/record.url?scp=84868265822&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-34222-6_18
DO - 10.1007/978-3-642-34222-6_18
M3 - Conference contribution
AN - SCOPUS:84868265822
SN - 9783642342219
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 214
EP - 219
BT - Provenance and Annotation of Data and Processes - 4th International Provenance and Annotation Workshop, IPAW 2012, Revised Selected Papers
T2 - 4th International Provenance and Annotation Workshop, IPAW 2012
Y2 - 19 June 2012 through 21 June 2012
ER -