Full Life Cycle of Data Analysis with Climate Model Diagnostic Analyzer (CMDA)
Abstract
We have developed a system that supports the full life cycle of a data analysis process, from data discovery, to data customization, to analysis, to reanalysis, to publication, and to reproduction. The system called Climate Model Diagnostic Analyzer (CMDA) is designed to demonstrate that the full life cycle of data analysis can be supported within one integrated system for climate model diagnostic evaluation with global observational and reanalysis datasets. CMDA has four subsystems that are highly integrated to support the analysis life cycle. Data System manages datasets used by CMDA analysis tools, Analysis System manages CMDA analysis tools which are all web services, Provenance System manages the meta data of CMDA datasets and the provenance of CMDA analysis history, and Recommendation System extracts knowledge from CMDA usage history and recommends datasets/analysis tools to users. These four subsystems are not only highly integrated but also easily expandable. New datasets can be easily added to Data System and scanned to be visible to the other subsystems. New analysis tools can be easily registered to be available in the Analysis System and Provenance System. With CMDA, a user can start a data analysis process by discovering datasets of relevance to their research topic using the Recommendation System. Next, the user can customize the discovered datasets for their scientific use (e.g. anomaly calculation, regridding, etc) with tools in the Analysis System. Next, the user can do their analysis with the tools (e.g. conditional sampling, time averaging, spatial averaging) in the Analysis System. Next, the user can reanalyze the datasets based on the previously stored analysis provenance in the Provenance System. Further, they can publish their analysis process and result to the Provenance System to share with other users. Finally, any user can reproduce the published analysis process and results. By supporting the full life cycle of climate data analysis, CMDA improves the research productivity and collaboration level of its user.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFMIN21D0063L
- Keywords:
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- 1626 Global climate models;
- GLOBAL CHANGE;
- 1920 Emerging informatics technologies;
- INFORMATICS;
- 1932 High-performance computing;
- INFORMATICS;
- 1994 Visualization and portrayal;
- INFORMATICS