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
Changes in Air Quality Management
Command & Control
Weight of Evidence
Flexible NAAMS
Rigid Monitoring
Real-time Air Pollution Sensing and Reporting
High Resolution Satellite DataSurface PM25 and Ozone Data
Smoke Plumes
Generic Decision Support for Air Quality Decisions
GEOSS Architecture Framework
Knowledge into the Minds of
Regulatory Analysts
Knowledge into the Minds of Technical Analysts
Observations
Reports:Model Forecasts,
Obs. EvidenceModels
DecisionsKnowledge
into the Minds of Decision- making
managers
Decision Support System
Key Technical Challenge: Characterization
• Pollutant characterization requires many different instruments and analysis tools.
• Each sensor/network covers only a fraction of the 6-8 dimensional data space.
• Other sensors provide only integral measures of the pollution, e.g. satellite - vertical integral.
Satellite-Integral
• Data are distributed geographically by autonomous providers
Emission
AmbientSatellite
Model
EPA
NOAA
NASAOther
Content | Agency | Form
• Data includes emissions
Emission
Emission
Emission
Emission
Emission
AmbientSatellite
Model
EPA
NOAA
NASAOther
Content | Agency | Form
Information Providers: Geography, Content, Agency, Form
• Data includes emissions, ambient data,
Ambient
Ambient
Ambient
Ambient
Emission
Emission
Emission
Emission
Emission
AmbientSatellite
Model
EPA
NOAA
NASAOther
Content | Agency | Form
• Data includes emissions, ambient data, satellite data
Satellite
Satellite
SatelliteSatellite
Ambient
Ambient
Ambient
Ambient
Emission
Emission
Emission
Emission
Emission
AmbientSatellite
Model
EPA
NOAA
NASAOther
Content | Agency | Form
• Data includes emissions, ambient data, satellite data and model output
Model
Model
ModelModel
Satellite
Satellite
SatelliteSatellite
Ambient
Ambient
Ambient
Ambient
Emission
Emission
Emission
Emission
Emission
AmbientSatellite
Model
EPA
NOAA
NASAOther
Content | Agency | Form
• Data are provided by multiple agencies: EPA, NOAA, NASA and others
NASAMission
NOAAGASP
NASAIDEA
NASA DAACs
NOAA ASOS
EPA-AQSDataMart
EPA AIRNow
RPO VIEWS
FS FireInv
State/LocalEmission
EPA NEISGEI
EPA NEI
NOAA WeaMod
EPAAQModel
NOAA Forecast
Emission
AmbientSatellite
Model
EPA
NOAA
NASAOther
Content | Agency | Form
NASA DAACs
NOAA GASP
NASAIDEA
NASA Missions
EPA NEI
EPA NEISGEIFS
FireInv
State/Local Emission
NOAA ASOS
RPO VIEWS
EPA AIRNow
EPA-AQS AIRS
NOAA WeaMod
EPA AQModel
NASA GloModel
NOAA Forecast
• Furthermore, data are provided in varied formats and access protocols
Emission
AmbientSatellite
Model
EPA
NOAA
NASAOther
Content | Agency | Form
• Data on Internet are geography-independent and can be ‘linearized’
Internet
NASA DAACs
EPA R&DModel
EPA AIRNow
others
• Users are distributed geographically
EPA
NOAA
NASAOther
Stakeholder | Agency | Form
Policy
Manager
Public
Scientist
EPA
NOAA
NASAOther
Stakeholder | Agency | Form
Policy
Manager
Public
Scientist
Policy
Policy
Policy
• Users includes policy makers
EPA
NOAA
NASAOther
Stakeholder | Agency | Form
Policy
Manager
Public
Scientist
• Users includes policy makers, the public
Policy
Policy
Policy PublicPublic
EPA
NOAA
NASAOther
Stakeholder | Agency | Form
Policy
Manager
Public
Scientist
• Users includes policy makers, the public, AQ managers
Policy
Policy
Policy PublicPublic
Manager Manager
EPA
NOAA
NASAOther
Stakeholder | Agency | Form
Policy
Manager
Public
Scientist
and scientist
Policy
Policy
Policy PublicPublic
Manager ManagerScientist Scientist
Scientist
EPA
NOAA
NASAOther
Stakeholder | Agency | Form
Policy
Manager
Public
Scientist
• Users are affiliated with multiple agencies: EPA, NOAA, NASA, as well as others
Policy
Policy
Policy PublicPublic
Manager ManagerScientist Scientist
Scientist
EPA
NOAA
NASAOther
Stakeholder | Agency | Form
Policy
Manager
Public
Scientist
Users: By Types, Agency, Info Needs
• Furthermore, users need various types of information provided in multiple formats
Policy
Manager
Policy
Scientist
ManagerScientistScientist
Policy
Public Public
EPA
NOAA
NASAOther
Stakeholder | Agency | Form
Policy
Manager
Public
Scientist
• Since the users are also on the Internet, their geographic location is irrelevant
Public
Manager
Scientist
Internet
other
• 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
ScientistScienceDAACs
• 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
DataData Program
ProgramOrganizatio
nDataData
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 ofEPA Analysts
Knowledge into the Minds of
State Analysts
DSS for Exceptional Event Decisionsapping of
Observations
Event Reports:Model Forecasts,
Obs. EvidenceModels
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. ProcessingSt
d.
Inte
rfac
e
Data
Control
Reports
Reporting
Obs. & Models Decision Support System
AnalyzingFilter/IntegrateAggregate/FuseCustom Analysis
OrganizingDocumentStructure/FormatInterfacing
CharacterizingDisplay/BrowseCompare/Fuse Characterize
Valu
e-Ad
ding
Pr
oces
ses 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 St
d.
Inte
rfac
e
Client
Front EndSt
d.
Inte
rfac
e
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. ProcessingSt
d.
Inte
rfac
e
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. ProcessingSt
d.
Inte
rfac
e
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. ProcessingSt
d.
Inte
rfac
e
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.