Transcript Slide 1 - VIEWS - Visibility Information Exchange Web System

Integrated Decision Support:
A Tale of Two Systems
VIEWS
The Visibility Information Exchange Web System
http://vista.cira.colostate.edu/views
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Developed by the five Regional Planning Organizations (RPOs) in 2002
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Provides easy online access to a wide variety of air quality data
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Offers user-friendly tools for exploring, visualizing, and analyzing data
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The primary source for IMPROVE Regional Haze Rule data
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Over 1100 registered users
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Over 300 organizations, institutions, and companies represented
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Developed for RPOs, States, Tribes, Federal Land Managers, and local agencies
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Used by researchers, analysts, planners, regulators, stakeholders, and students
TSS
Technical Support System
http://vista.cira.colostate.edu/tss
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Built upon the database and software infrastructure of VIEWS
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Developed initially for Western States, Tribes, and air quality agencies
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Provides a access point for regional technical data, guidance, and results
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Offers tools and support for the development of SIPs and TIPs
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Documents the technical methods used in implementation plans
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Helps assess the impact of other areas on local Class I Areas
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Provides ongoing tracking and assessment of emissions control strategies
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Will adapt to and serve the future regional technical needs of WRAP members
VIEWS/TSS Data Value Chain
Verification
Validation
Standardization
Conclusions
Comparison
Modeling
Assessment
Regulations
Transformation
Normalization
Aggregation
Data Collection
Data
Primary Storage
Aggregation, Integration,
Processing, Modeling
Processing
Analysis
Forecasting
Reanalysis
Analysis, Visualization, Reporting
Analysis
Recommendations
Decision Support
End Users
Decisions
Verification
Validation
Standardization
Conclusions
Comparison
Modeling
Assessment
Regulations
Transformation
Normalization
Aggregation
Data Collection
Data
Primary Storage
Aggregation, Integration,
Processing, Modeling
Processing
Analysis
Forecasting
Reanalysis
Analysis, Visualization, Reporting
Analysis
Recommendations
Decision Support
End Users
Decisions
VIEWS/TSS Data Inventory
VIEWS/TSS Data Inventory
VIEWS/TSS Data Inventory
Verification
Validation
Standardization
Conclusions
Comparison
Modeling
Assessment
Regulations
Transformation
Normalization
Aggregation
Data Collection
Data
Primary Storage
Aggregation, Integration,
Processing, Modeling
Processing
Analysis
Forecasting
Reanalysis
Analysis, Visualization, Reporting
Analysis
Recommendations
Decision Support
End Users
Decisions
VIEWS/TSS Data Processing: Import & Validation
Validation
Metadata Import System
Data
Acquisition
System
Data Import System
AIRDATA_SOURCE
AIRDATA_OLTP
Validation
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Data Acquisition System
Metadata Import System
Emailed updates from data providers ·
Automatic HTTP extraction of source
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data files
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Database replication
Imports data “as-is” into the source
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database
Technologies: ASCII text files, Excel
spreadsheets, Access databases, etc.
Facilitates the entry of new
metadata
Validates new metadata entries
Detects overlap with existing
metadata
Technologies: VB .Net, ASP .Net,
and SQL Server stored procedures
Data Import System
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Extracts data from the source database
Scrubs data and performs conversions
Maps source metadata to integrated metadata
Transforms the data into an integrated schema
Verifies and validates imported data
Loads data into the back-end OLTP system
Technologies: Microsoft SQL Server DTS,
stored procedures, SQL scripts, and Visual
Basic routines
VIEWS/TSS Data Processing: Integration
OLTP:
Data Warehouse Generation System:
Data Warehouse:
• Functions as the “back-end” database
• Fully relational and in 3rd normal form
• Used for data import, validation, and
management
• Technologies: Microsoft SQL Server
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Extracts data from the OLTP
De-normalizes and transforms data
Loads data into the Data Warehouse
Builds table indexes
Archives “snapshots” of the database
Technologies: VB, stored procedures
Functions as the “front-end” database
Uses a de-normalized “star schema”
Used for querying and archiving data
Automatically generated from the OLTP
Technologies: Microsoft SQL Server
Verification
Validation
Standardization
Conclusions
Comparison
Modeling
Assessment
Regulations
Transformation
Normalization
Aggregation
Data Collection
Data
Primary Storage
Aggregation, Integration,
Processing, Modeling
Processing
Analysis
Forecasting
Reanalysis
Analysis, Visualization, Reporting
Analysis
Recommendations
Decision Support
End Users
Decisions
VIEWS/TSS Analysis Tools: Dynamic Contour Maps
VIEWS/TSS Analysis Tools: Dynamic Data Maps
VIEWS/TSS Analysis Tools: Network Inter-comparison
Parameter: Nitrate Ion Concentrations
Location: Bondville, IL
Networks: IMPROVE, STN, and CASTNet
Graphs: Time Series and Scatter Plot
VIEWS/TSS Tools: Model Performance Evaluation
CMAQ Model Performance vs. Monitored Worst 20% Days in 2002
VIEWS/TSS Analysis Tools: Source Apportionment
 Mass source apportionment by source
category and region
 From regional photochemical model with
comprehensive emissions inputs
 Species mass for various time periods –
directly comparable to monitoring data
VIEWS/TSS Analysis Tools: Glide Slope
VIEWS/TSS Analysis Tools: Multidimensional Analysis
 Multiple NAAQS indicators, multiple time periods, multiple locations
 Displayed with consistent, comparable graphics in the same tool
VIEWS/TSS Analysis Tools: Emissions Review Tool
• Available Parameters:
– Sulfur Dioxide
– Sulfur Oxides (gas and
particulate)
– Nitrogen Oxides (gas)
– Nitrogen Oxides (gas and
particulate)
– Other species from SMOKE
• Multiple dimensions:
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Parameters
Emissions Scenarios
Source Categories
Regions of Interest
• Future plans:
– Display regional summaries as
well as state-level emissions
VIEWS/TSS Tools: Raw Data
VIEWS/TSS Tools: Connections to Other Systems
VIEWS/TSS Interoperability
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Import and output data in common formats, by standard protocols
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K.I.S.S. – Because users like to do odd things with data
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Practice a “Service Oriented Architecture” approach
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Develop reusable, “component” tools
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Make interoperability an important goal, while resisting the urge to
develop the “Ultimate All-Things-to-All Users” type of system
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Adhere to sound software and system architecture principles
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Allow direct, read-only access to our database
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Support and promote an open data and software architecture
Verification
Validation
Standardization
Conclusions
Comparison
Modeling
Assessment
Regulations
Transformation
Normalization
Aggregation
Data Collection
Data
Primary Storage
Aggregation, Integration,
Processing, Modeling
Processing
Analysis
Forecasting
Reanalysis
Analysis, Visualization, Reporting
Analysis
Recommendations
Decision Support
End Users
Decisions
VIEWS/TSS Decisions: Benefactors & Benefits
Federal Land Managers:
States, Tribes, and Local Agencies:
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• Effective Implementation Plans
• Defensible and achievable control
strategies
• Uniform and reasonable progress
• Better air quality in Class I Areas
Better air quality evaluation
More accurate source apportionment
More meaningful impact assessment
Informed permitting and regulation
Improved air quality in ecosystems
EPA and RPOs:
General Air Quality Community:
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• Better insight into the decision process
• Real life evidence of successes &
failures
• Incorporation of feedback into next
generation products
• Increasing expertise in developing
decision support tools
Effective emissions control evaluation
Practical and equitable standards
Leveraging of existing efforts
Improved synergy with States and Tribes
Valuable case studies and precedents
More effective application of resources
VIEWS/TSS Team: Future Plans
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Add satellite data in conjunction with NASA ROSES contract
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Add additional NAAQS (ozone, for example) and global data
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Develop more tools that offer region- and locale-specific analyses
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Develop appropriate new functionality as web services
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Refine decision tools for making interpretations and recommendations
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Expand and refine guidance documentation
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Establish case studies from the user community as guidance
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Allow users to upload and immediately work with their data
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Develop modular, reusable, components for other developers
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Establish reusable precedents for air quality decision support
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Have a few beers every once (or twice) in a while…
Decisions
(interpretations, conclusions, guidelines, regulations
Raw data
(observations, methods)
Science
(knowledge, examples,
expertise, theory)
Processed data
Analysis
(calculated, RHR,
normalized, value-added)
(Tools, reanalysis, modeling,
inputs from other systems)
The End…
Thanks!