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16 months…

Explore VIEWS, a database system supporting air quality research with tools for analysis and access to millions of air data records. Learn about its goals, structure, and architecture details.

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16 months…

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  1. 16 months…

  2. VIEWS: An Approach to Air Quality Data Management What is VIEWS? Some facts: The Visibility Information Exchange Web System is a database system and set of online tools originally designed to support the Regional Haze Rule enacted by the EPA to reduce regional haze in national parks and wilderness areas. • Over 600 registered users • Over 200 organizations represented • Almost 100 countries represented • 300+ unique hits a day • Linked to by over four dozen sites • Over 40 million records of air data • Dozens of monitoring networks • CSU Research Initiative Award • Uses the new Manifold GIS • Monitoring site photographs • Class I Area webcams • Visibility photographs • Visibility Grey Literature • Periodic Newsletter • Contour Maps • Trends Analysis • Air Mass Composition Analysis What are some of its other goals? • Provide easy online access to a wide variety of air quality data. • Provide online tools for exploring and analyzing this data. • Maintain a catalog of relevant air quality-related resources. • Facilitate the research and understanding of global air quality issues. Web Address: Sponsor: Guiding Body: Location: Staff: Affiliations: http://vista.cira.colostate.edu/views Five EPA Regional Planning Organizations (RPOs) VIEWS Steering Committee Cooperative Institute for Research in the Atmosphere (CIRA), Colorado State University, Fort Collins, CO Scientists, researchers, and IT professionals Interagency Monitoring of Protected Visual Environments (IMPROVE)

  3. “VIEWS-based” web sites... VIEWS ATDA IMPROVE

  4. Dataset Inventory

  5. VIEWS Software Infrastructure: Highlights • Common databases, documents, and other resources • Common data access layer (same queries and “plumbing”) • Common interface elements (list boxes, charts, graphs, tables) • Common website organization (navigation, file structure, features) • Modular and interoperable software components • Standardized data exchange protocols • Resources and tools implemented as XML Web Services

  6. VIEWS Architecture Detail: Overview Import Validation Storage Retrieval Presentation Transformation Source Data Database Rules Source Data Analysis Interpretation Program Logic Source Data Front End Back End Import: Getting data into the system Validation: Ensuring data accuracy Storage: Managing data, backup, and archival Transformation: Sorting, joining, aggregating Retrieval: Getting the data out Presentation: Displaying the data Analysis: Making the data understandable Interpretation: Making the data usable VIEWS Architecture Overview

  7. VIEWS Architecture Detail: Data Acquisition & Import 7 • Data Acquisition System: • Accepts submission of data in a variety of schemas and formats • Can automatically extract data from known online sources • Uses database replication where possible • Initially imports data and metadata “as-is” into the source database • Metadata Import System: • Facilitates the entry of new metadata • Validates new metadata entries • Detects overlap with existing metadata • Data Import System: • 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

  8. VIEWS Architecture Detail (cont’d): Data Management 8 • OLTP: • Functions as the “back-end” database • Fully relational and in 3rd normal form • Used for data import, validation, and management • Technologies: Microsoft SQL Server • Data Warehouse Generation System: • 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 • Data Warehouse: • 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 8

  9. 16 months…

  10. VIEWS Architecture Detail (cont’d): Data Presentation and Analysis

  11. VIEWS Architecture Detail (cont’d): Data Presentation and Analysis

  12. TSS: Development Thoughts • Define a reasonable scope of work • Carefully prioritize milestones and products • Design an intuitive format and organization for portal & its products • Define a common interface for product input parameters • Strike a realistic balance between "static" and "dynamic" products • Provide for multiple phases of prototyping • Determine a successful method for gathering useful feedback • Thoroughly document methods & procedures for producing products • Concentrate on products, not tools (at least for this phase) • Overestimate the time cost of coordination • Err on the side of simplicity…

  13. 16 months… http://vista.cira.colostate.edu/views

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