Architecture and Technologies for an Agile, User-Oriented Air Quality Data System

Rudolf B. HusarWashington University, St. Louis

Presented at the workshop The User and the GEOSS Architecture

Applications for North AmericaJuly 30, 2006, Denver

Outline

• Highlight Trends of Air Quality Sensing and Management• Describe an Agile IS Architecture for Air Quality Decision Support • Show Their Application Through Two Use Cases

• The data life cycle consists of the acquisition and the usage parts

Usage ActivitiesData Acquisition

Data Acquisition and Usage Activities(Select View Show, click to step through PPT)

• The acquisition part processes the sensory data by firmly linked procedures

The focus is on data usage activities

• The usage activities are more iterative, dynamic procedures

• The collected and cleaned data are stored in the repository

Data Repository

• The usage cycle transform data into knowledge for decision making

Decisions

ScientistScience

DAACs

• Current info systems are project/program oriented and provide end-to-end solutions

Info UsersData Providers Info System

AIRNowPublicAIRNow

ModelCompliance

Manager

‘Stovepipe’ and Federated Usage Architectures Landscape

• Part of the data resources of any project can be shared for re-use through DataFed

• Through the Federation, the data are homogenized into multi-dimensional cubes

• Data processing and rendering can then be performed through web services

• Each project/program can be augmented by Federation data and services

The Network Effect:Less Cost, More Benefits through Data Multi-Use

ProgramPublic

Data Organization

Data

Data Program

Program

OrganizationData

Data

ProgramData

Orgs Develop Programs

Programs ask/get Data Public sets

up Orgs

Pay only once Richer content

Data Re-Use Network Effect

Data are costly resource – should be reused (recycled) for multiple applications

Data Reuse

Less Prog. Cost More Knowledge

Data reuse saves $$ to programs and allows richer knowledge creation

Less Soc. Cost More Soc. Benefit

Data reuse, like recycling takes some effort: labeling, organizing, distributing

Providers

NASA DAACs

EPA R&DModel

EPA AIRNow

others

Public

Manager

Scientist

Users

other

• The info system transforms the data into info products for each user • In the first stage the heterogeneous data are prepared for uniform access

Uniform Access

Agile Information System: Data Access, Processing and Products

• The second stage performs filtering, aggregation, fusion and other operations

Data Processing Web Service Chain

Custom Processing

SciFlo

DataFed

Info Products Reports, Websites

Forecasting

Compliance

Other

Sci. Reports

• The third stage prepares and delivers the needed info products

Decision Support System

Event Knowledge into the Minds of

EPA Analysts

Knowledge into the Minds of

State Analysts

DSS for Exceptional Event Decisionsapping of

Observations

Event Reports:Model Forecasts,

Obs. Evidence

Models

DecisionsEvent Knowledge into the Minds of

EPA Regulators

Decision Support System

Data Sharing

Std

. In

terf

ace

Data

Obs. & Models

Characterization

Std

. In

terf

ace

ReportingDomain Processing

ControlReports

Stages of AQ Data Flow and Value-Adding Processes

Domain ProcessingData Sharing

Std

. In

terf

ace

Gen. ProcessingS

td.

Inte

rface

Data

Control

Reports

Reporting

Obs. & Models Decision Support System

Analyzing

Filter/IntegrateAggregate/FuseCustom Analysis

Organizing

DocumentStructure/FormatInterfacing

Characterizing

Display/BrowseCompare/Fuse Characterize

Valu

e-A

dd

ing

P

rocesses

Reporting

Inclusiveness Iterative/Agile Dynamic Report

Loosely Coupled Data Access through Standard Protocols

The next three slides describe the key technologies used in the creation of an adaptable and responsive air quality information system.

OGC data access protocols and standard formats facilitate loose coupling between data on the internet and processing services.

For air quality, the Web Coverage Service (WCS), provides a universal simple query language for requesting data as where, when, what. That is: geographic (3D bounding box), time range and parameter.

The Web Map Service (WMS) and Web Feature Service (WFS) are also useful.

The use of standard data physical data formats and naming conventions elevates the syntactic and semantic interoperability.

Within DataFed all data access services are implemented as WCS or WMS and optionally WFS. General format adapter components permit data request in a variety of standard formats.

GetCapabilities

GetData

Capabilities, ‘Profile’

Data

Where? When? What? Which Format?

Server

Back End S

td.

Inte

rface

Client

Front EndS

td.

Inte

rface

Query GetData Standards

Where? BBOX OGC, ISO

When? Time OGC, ISO

What? Temperature CF

Format netCDF, HDF.. CF, EOS, OGC

T2T1

Domain ProcessingData Sharing

Std

. In

terf

ace

Gen. ProcessingS

td.

Inte

rface

Data

Control

Reports

Reporting

Obs. & Models Decision Support System

Web Services and Workflow for Loose Coupling

Service Broker

Service Provider

PublishFind

BindServiceUser

Web Service Interaction Service Chaining & Workflow

Domain ProcessingData Sharing

Std

. In

terf

ace

Gen. ProcessingS

td.

Inte

rface

Data

Control

Reports

Reporting

Obs. & Models Decision Support System

Web Services Triad:Publish – Find – Bind

Workflow Software:Dynamic Programming

Collaborative Reporting and Dynamic Delivery

Co Writing - Wiki

ScreenCast

Analysis Reports:

Information supplied by manyNeeds continuous program feedbackReport needs many authorsWiki technologies are for collaborative writing

Dynamic Delivery:

Much of the content is dynamicAnimated presentations are compellingMovies and screencasts are for dynamic delivery

Domain ProcessingData Sharing

Std

. In

terf

ace

Gen. ProcessingS

td.

Inte

rface

Data

Control

Reports

Reporting

Obs. & Models Decision Support System

Summary

• The current challenges for air quality information systems include delivery of air quality data in real time, characterization of air pollution through the integration of multi-sensory data and providing agile support to regulatory management. The talk describes the architecture and implementation of a standards based system for accessing and processing air quality data. The web services based architecture is illustrated through two use cases: (1) real time monitoring of a smoke event and (2) hemispheric transport of air pollutants.

Acknowledgements

• The presentation on Air Quality Background and Information Architecture benefited greatly from ideas, and challenges posed by a number of experienced individuals, from EPA (Rich Scheffe, Steve Young, Terry Keating), NASA (Lawrence Friedl, Kathy Fontaine). The participation in the NASA Information Technology Infusion workgroup (Karen Moe, Bran Wilson, Liping Di and others) was an intense collective learning experience. At CAPITA, Kari Hoijarvi engineered and implemented DataFed; Stefan Falke contributed datasets and application software.