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