Visibility Information Exchange Web System

Source Data Import Source Data Validation Database Rules Program Logic Storage RetrievalPresentation AnalysisInterpretation Transformation Import: Getting the data into the system Validation: Ensuring data accuracy Storage: Managing the data, backup, archival Transformation: Sorting, joining, aggregating Retrieval: Getting the data out Presentation: Displaying the data Analysis: Making the data understandable Interpretation: Making the data usable Evaluating 

Represents data in a way easily dealt with by people Database organization resembles a star Strengths: Easier to understand and access by direct users Queries are simplified and tend to be faster Ideal for front-end functions Weaknesses: Harder to manipulate programmatically Harder to import, validate, and transform data Cumbersome for back-end functions Supporting Dimension tables Contain metadata and other support data Networks, Sites, Parameters, Methods, Time Intentionally “flat”  one level of relationships Redundant data and redundant relationships Decision Support System (DSS) design Central Fact table Contains actual air observation values Maintains links to all dimension tables Networks SitesParameters MethodsTime Air_Obs Options 

Leverage the Existing Architecture Pros: Less up-front time and effort Reuses the existing design Cons: Not easily scalable Programmatic manipulation is harder Doesn’t address back-end functions Extend and Enhance the Existing Architecture Pros: Realizes more back-end functions Still involves only one database design Cons: A specialized, unconventional design Harder to understand, maintain, & scale Implement a Separate Architecture for Back-end Support Pros: Full Support of back-end functions Machine-friendly, easier to automate Allows both designs to be optimized Keeps logical operations separate Long-term scalability and flexibility Cons: Requires greater initial development effort Two distinct architectures to maintain * * Not Really  stay tuned… Analyzing 

Measurements of sets of parameters, taken at certain geographical locations, with particular instruments, on specific dates and at given times, which are then analyzed, recorded, and disseminated as data. What sentence best describes the data and data flows of the system? What is the “common currency” of the system ? The Sample What is the “primary mediator” of the system ? The Instrument What are the “entities” of the system ? Locations (Sites), Parameters, Methods, Date/Time What are the “primary actions” of the system ? Analyzing, Recording Implementing 

Represents data in a way easily dealt with by machines The Online Transaction Processing System (OLTP) … Technical Characteristics Fully relational and completely normalized Optimized for insert, update, and delete Allows more efficient indexing Larger number of tables and relationships Automatically enforces referential integrity Description and Functional Characteristics Facilitates importing data into the system Promotes data integrity and facilitates validation Makes storage more efficient Speeds and simplifies transformation Additional Benefits and Considerations Scalability: Will handle more data and users without changing the design Interoperability: Interacts more easily with other systems and datasets Maintenance: Facilitates modification, upgrade, and enhancement Security: Facilitates backup, recovery, archival, and integrity Leveraging 

The front-end DSS is automatically generated by the back-end OLTP Final Notes Map Projection Analogy: Base system (globe) and derived views (projections) Optimization: Allows each architecture to do what it does best without compromise Data Transparency: User doesn’t need to know how data is stored, only how to use it Exchangeability: A wide variety of diverse schemas can be generated from OLTP Networks SitesParameters MethodsTime Air_Obs SQL Script Generation of the Front End : Periodically On Demand Future 

Fully automate data import and validation Provide data products as web services for users, models, and programs Reduce the need for local data storage and maintenance Promote the free exchange of data and ideas Provide enhanced metadata browsing Facilitate GIS integration Provide presentation-ready data products Facilitate RPO support of the Regional Haze Rule Thank you for your attention…