Metadata Catalog Optimization for Heterogeneous Near-Real-Time Earth System Data

Authors: Juozas Gaigalas*,
Topics: Geographic Information Science and Systems, Cyberinfrastructure, Climatology and Meteorology
Keywords: big data, geographic information systems, climate, earth system modeling
Session Type: Guided Poster
Day: 4/4/2019
Start / End Time: 3:05 PM / 4:45 PM
Room: Roosevelt 3.5, Marriott, Exhibition Level
Presentation File: No File Uploaded

The Earth System is dynamic complex system of interconnected by feedback loops. This system is undergoing significant changes in its dynamics that are driven by human activities, such as emissions of green house gases. We understand that these changes will be drastic, but our efforts to predict specific details and areas impacted are advanced but not very accurate. A major obstacle to better understanding is the complexity, variety and volume of data generated and consumed being consumed. Collaboration across scientific disciplines requires researchers to access and utilize data generated in unfamiliar domains. Once data barriers to cross-domain collaboration are lowered we expect that new and more accurate scientific understanding of climate will emerge.

To support data collaboration, many online metadata repositories have been created. This metadata describes the characteristics of Earth observation and model data products, such as variables studied, temporal and spatial extents, authorships and other relevant information. These catalogs exist to enable search, discovery and access of unfamiliar data. They utilize standard schemas to promote interoperability. However, their varied structure adds additional complexity and does not facilitate simple access and integration with existing data. Furthermore, the catalogs tend to publish redundant metadata that consumes computing resources without adding new information. This poster discusses analysis and automatic processing strategies applied to enable simultaneous integrated search of UCAR long-term archive, forecast model and near-real-time radar metadata.

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