Several recent advancements in science can be attributed to our ability to discover, share, integrate and analyze data. Creating a mechanism to achieve data discoverability and interoperability across scientific domains and data systems can be initially overwhelming. We use the Terrestrial Observation and Prediction System (TOPS), a data and modeling software system designed to generate and integrate data from numerous sources, OpenModeller, a fundamental niche modeling system for species distribution prediction, and the Open geospatial consortium (OGC) web coverage service (WCS) 1.0 protocol specification for model data exchange. TOPS provided approximately 225 statistically downscaled Global Circulation Model (GCM) runs from the Intergovernmental Panel on climate Change (IPCC) 4th assessment data archive. The GCM data were downscaled, repackaged and served via a lightweight WCS server with spatial and temporal sub- setting capabilities. OpenModeller, which was executed by an external group, leveraged the climatic scenarios provided by the TOPS WCS server to drive a niche model and produce an ensemble of species distribution predictions. The value added by TOPS downscaling and its capability to provide coverage's for specific time ranges and areas of interest was significant. This exercise shows that when geospatial information sources and models enter into a loosely coupled interoperable environment, using a standardnificant. This exercise shows that when geospatial information sources and models enter into a loosely coupled interoperable environment, using a standards-based approach, it is not difficult for modeling systems to utilize valuable services provided by external entities that are otherwise not available "in house".
A Model Web Interoperability Experiment Using The Terrestrial Observation and Prediction System and OpenModeller
Nativi S
2008
Abstract
Several recent advancements in science can be attributed to our ability to discover, share, integrate and analyze data. Creating a mechanism to achieve data discoverability and interoperability across scientific domains and data systems can be initially overwhelming. We use the Terrestrial Observation and Prediction System (TOPS), a data and modeling software system designed to generate and integrate data from numerous sources, OpenModeller, a fundamental niche modeling system for species distribution prediction, and the Open geospatial consortium (OGC) web coverage service (WCS) 1.0 protocol specification for model data exchange. TOPS provided approximately 225 statistically downscaled Global Circulation Model (GCM) runs from the Intergovernmental Panel on climate Change (IPCC) 4th assessment data archive. The GCM data were downscaled, repackaged and served via a lightweight WCS server with spatial and temporal sub- setting capabilities. OpenModeller, which was executed by an external group, leveraged the climatic scenarios provided by the TOPS WCS server to drive a niche model and produce an ensemble of species distribution predictions. The value added by TOPS downscaling and its capability to provide coverage's for specific time ranges and areas of interest was significant. This exercise shows that when geospatial information sources and models enter into a loosely coupled interoperable environment, using a standardnificant. This exercise shows that when geospatial information sources and models enter into a loosely coupled interoperable environment, using a standards-based approach, it is not difficult for modeling systems to utilize valuable services provided by external entities that are otherwise not available "in house".I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
