NASA REASoN Project SHAirED: S ervices for H elping the Air -quality Community use E SE D ata Stefan Falke, Kari Höijärvi and Rudolf Husar, Washington.

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NASA REASoN Project SHAirED: S ervices for H elping the Air -quality Community use E SE D ata Stefan Falke, Kari Höijärvi and Rudolf Husar, Washington University, St. Louis Description & Objectives Approach Partners: NASA-Langley, EPA-OAQPS, RPOs Develop data access services for interrogating their spatial, temporal, and parameter dimensions. Currently in TRL 4. Develop data processing and analysis web services. Currently in TRL 4/5 Chain web services together to create dynamic applications. Currently in TRL 3 Deliver and use Earth Science Enterprise (ESE) data and tools in support of particulate air quality management and develop a federated PM information sharing network that includes data from NASA, EPA, and US States. SHAirED will: develop access to distributed data (surface and satellite), build Web infrastructure create tools for data processing and analysis. The key technologies used in the project include web services for developing data access and processing tools, and service oriented architecture for chaining web services together to assemble customized applications. DataFed provides the web infrastructure that supports collaborative atmospheric data sharing and development of processing web services. A primary objective of SHAirED is to develop new IT that advances the TRL of DataFed. October 2004 Applications – Integration of satellite imagery with surface data and model output in air quality research and management, such as real-time aerosol tracking and smoke management

NASA REASoN Project SHAirED: S ervices for H elping the Air -quality Community use E SE D ata Stefan Falke, Kari Höijärvi and Rudolf Husar, Washington University, St. Louis October 2004

Wrappers Turn data access into services Web Services Reusable, chainable ‘Lego’ software blocks Chaining Applications from loosely coupled blocks

AQ DATA EPA Networks IMPROVE Visibility Satellite-PM Pattern METEOROLOGY Met. Data Satellite- Transport Forecast model EMISSIONS National Emissions Local Inventory Satellite Fire Locs Status and Trends AQ Compliance Exposure Assess. Network Assess. Tracking Progress AQ Management Reports ‘Knowledge’ Derived from Data Primary Data Diverse Providers Data ‘Refining’ Processes Filtering, Aggregation, Fusion Web Services Data Flow & Processing in AQ Management Driving Forces: Provider Push User Pull Resistances: Data Access Processing Delivery

Service Oriented Architecture: Data AND Services are Distributed Control Control DataData ProcessProcess ProcessProcess ProcessProcess Peer-to-peer network representation DataData ServiceService CatalogCatalog ProcessProcess Data, as well as services and users (of data and services) are distributed Users compose data processing chains form reusable services Intermediate and resulting data are also exposed for possible further use Processing chains can be further linked into complex value-adding data ‘refineries’ Service chain representation User Tasks: Fi nd data and services Compose service chains Expose output Chain 2Chain 2 Chain 1Chain 1 Chain 3Chain 3 DataData ServiceService User Carries less Burden In service-oriented peer-to peer architecture, the user is aided by software ‘agents’

DataView 1 Physical Data Abstract Data Abstract data slices are requested by viewers; uniform data are delivered by wrapper services DataView 2 DataView 3 View Data Processed data are delivered to the user as multi-layer views by portrayal and overlay web services Processed Data Data passed through filtering, aggregation, fusion and other processing web services Generic Data Flow and Processing for Analysis Multi-Dimensional Data Model

A Wrapper Service: TOMS Satellite Image Data Through the wrapper service, TOMS images are accessed, georeferenced, subset, overlaid, etc.. The wrapping is ‘non-intrusive’, i.e. the provider does not have to adopt. Hence, interoperability (value) can be added independently, retrospectively and by 3 rd party src_img_width src_margin_right t src_margin_left src_margin_top src_lon_min src_lat_max src_lat_min src_lon_ma x The daily TOMS ftp://toms.gsfc.nasa.gov/pub/eptoms/images/aerosol/y2000/ea gif ftp://toms.gsfc.nasa.gov/pub/eptoms/images/aerosol/y2000/ea gif Data Access Template: ftp://toms.gsfc.nasa.gov/pub/eptoms/images/aerosol/y[yyyy]/ea[yy][mm][dd].gif