The Visibility Information Exchange Web System (VIEWS): An Approach to Air Quality Data Management and Presentation In a broader sense, VIEWS facilitates the research and understanding of air quality issues in general. To fulfill these goals, the VIEWS team developed a generalized relational data model for air quality data and implemented a database system, website, and supporting software infrastructure for importing, managing, and presenting air quality data from a wide variety of sources. A primary focus of these efforts was to design a system capable of integrating diverse data sets into a common schematic and semantic framework in order to more easily manage and compare the constituent data. The data model was designed to support the mapping of source metadata onto a common collection of integrated metadata where possible, and an extensive software system was developed to import and transform the source data into a common relational schema while performing the associated metadata mappings. A carefully designed system of relational constraints and database rules was developed to ensure the accuracy, integrity, and relational consistency of all imported data. To make the data readily available for browsing, download, and analysis, the VIEWS team implemented a suite of online tools and resources in the form of the VIEWS website. Scientists, researchers, and policy makers from a broad range of organizations now use the website as a primary source of air quality data and resources. The VIEWS team intends to continually import new air quality data and improve its suite of tools for accessing and viewing this data.   Web Address:   Sponsor: Five EPA Regional Planning Organizations (RPOs)   Guiding Body: VIEWS Steering Committee   Location: Cooperative Institute for Research in the Atmosphere (CIRA), Colorado State University, Fort Collins, CO   Staff: Scientists, researchers, and IT professionals   Affiliations: Interagency Monitoring of Protected Visual Environments (IMPROVE) The Visibility Information Exchange Web System (VIEWS) is a database and website system that provides access to air quality data, data summaries, and research tools in support of the Regional Haze Rule enacted by the U.S. Environmental Protection Agency (EPA) to reduce regional haze in national parks and wilderness areas. Introduction Wet Deposition (NADP/NTN)   Aqueous rain water concentration (mg/L).   Precipitation weighted mean concentration (mg/L).   Deposition (kg/ha) - the product of aqueous SO4 2- concentration in collected rain water and total precipitation over a given time period (e.g. season, year). Dry Deposition (CASTNet)   Dry deposition (kg/ha) for atmospheric particles and gas phase species (e.g. SO2, HNO3, NH3) - the product of the species’ deposition velocity and the ambient air concentration integrated over time (e.g. season, year). Air Concentrations (IMPROVE, CASTNet, STN, other speciated networks)   Aerosol and gas phase air concentrations (ug/m3). Inter-comparisons (Sulfur)   Compare raw concentration data (ug/m3 to mg/L)   Compare slopes in respective trends, for example S (SO2 plus SO4 2- ) air concentrations to S deposition expressed as %/season, %/yr. Conclusion With deposition data now incorporated into a common schematic and semantic format with aerosol data in the VIEWS database system, the issues involved in performing meaningful comparisons between the two types of data can be more easily identified, explored, and resolved. Data Acquisition System: Accepts submission of new data in a variety of formats Can automatically extract data from known online sources Uses database replication where possible Initially imports data “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 OLTP: Functions as the “back-end” database Fully relational and in third normal form Used for data import, validation, and management Data Warehouse Generation System: Extracts data from the OLTP De-normalizes and transforms data Archives snapshots of existing data Loads data into the data warehouse Builds indexes on relevant tables Data Warehouse: Functions a the “front-end” database Uses a de-normalized star schema Used for querying and archiving data Automatically generated from OLTP Backup and Restore System: Automatically and periodically backs-up critical VIEWS databases Restores database backups on demand Replication and Archival System: Vertically partitions the warehouse by time period Takes a full “snapshot” of the data warehouse at regular intervals Creates a historical audit trail for verifying archive integrity Data Acquisition: DTS Wizard used to import NTN Sites table DTS Wizard used to import NTN Data table NTN SOP information entered manually Metadata Import: Used SQL scripts to extract unique metadata from source data set Created new records for NTN metadata using the extracted source metadata Data Import: Used stored procedures and VB routines to transform the data from its source format Applied DB integrity constraints to verify the transformations Mapped source codes to relational primary keys (IDs) Loaded the results into a new table and validated the data using a series of row and column checksums and record counts NADP NTN Data Import Browsing NTN Metadata:A Basic Comparison between NTN and IMPROVE: Notes and Issues Regarding Comparisons Between Aerosol and Deposition Data: Some VIEWS Tools: Site Browser ASCII Files Metadata Browser Query Wizard Third Party Tools Webcams Resource Catalogs Annual Summary