Post on 31-Dec-2015
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.