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http://capitawiki.wustl.edu/index.php/20041015_SHAirED:_Services_for_Helping_the_Air-quality_Community_use_ESE_Data
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NASA REASoN Project
SHAirED: Services for Helping the Air-quality Community use ESE DataStefan 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: Services for Helping the Air-quality community use ESE DataStefan Falke, Kari Höijärvi and Rudolf Husar, Washington University in St. Louis
October 2004
SHAirED will: • develop access to distributed data (surface, satellite, model) • 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.
Objective: Deliver and use Earth Science Enterprise (ESE) data and tools in support of particulate air quality management and develop a federated AQ information sharing network that includes data from NASA, EPA, and US States.
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.
Web Application
• Develop data access services for spatial, temporal, and parameter queries. Current:TRL 4 Goal:TRL 7• Develop data processing and analysis web services. Current:TRL 4/5 Goal:TRL 7• Chain web services to create dynamic applications. Current:TRL 3 Goal:TRL 7
Approach:
WrappersTurn data
access into services
Web ServicesReusable, chainable
‘Lego’ software blocks
ChainingApplications 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
Data
Process Process
Process
Peer-to-peer network representation
Data ServiceCatalog
Process
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:
Find data and services
Compose service chains
Expose output
Chain 2
Chain 1 Chain 3
Data
Service
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
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The daily TOMS ftp://toms.gsfc.nasa.gov/pub/eptoms/images/aerosol/y2000/ea000820.gif
Data Access Template: ftp://toms.gsfc.nasa.gov/pub/eptoms/images/aerosol/y[yyyy]/ea[yy][mm][dd].gif