1. 1 st Quarter 2009 Status Update The Visibility Information Exchange Web System (VIEWS) Cooperative Institute for Research in the Atmosphere

2. 2007 NASA ROSES proposal EPA ozone and multiple pollutant project Recent collaborations and activities Interoperability efforts and connected systems Leveraging the VIEWS architecture Expanding the VIEWS team Hardware infrastructure update New VIEWS website coming Future goals and plans Annotated Screenshots Presentation Outline

3. Title: Improving Air Quality Analysis and Planning through the Integration of Satellite Data with Ground-based Observations, Modeling Results, and Emissions Estimates (Co-PIs: Shankar, McClure; awarded in 2008; work ongoing through 2011) Goals: Provide for the visualization and analysis of satellite data in combination with monitoring, modeling, and emissions data Develop routine capture, analysis, and processing algorithms with high temporal and spatial resolution in order to provide better land use/land cover model inputs Obtain finer temporal and spatial resolution of emissions data in remote areas and from individual sources and source clusters Improve boundary and other modeling inputs with four-dimensional pollutant data Evaluate gridded chemistry-transport models, such as CMAQ NASA ROSES Project: Overview

4. Conducted a project design workshop (May 2008, CIRA) Refined the project scope and plan Acquired the following datasets:  Aura OMI Level 2G  Aura OMI Level 3  Aqua MODIS Level 3  Terra MODIS Level 3  Terra and Aqua MODIS AOD on the CMAQ grid  CALIPSO Level 2 on a 12x12km CMAQ NCEP grid Explored the structure and organization of available data Identified the parameters to extract and/or utilize from the raw data Determined bandwidth and speed limits for data download operations Estimated storage requirements and data download frequencies Created a prototype visualization tool: http://vista.cira.colostate.edu/nasahttp://vista.cira.colostate.edu/nasa Created a project website and wiki: http://vista.cira.colostate.edu/airdatawikihttp://vista.cira.colostate.edu/airdatawiki NASA ROSES Project: CIRA activities so far

5. Goals: Evolve VIEWS into a multiple-pollutant data system Expand the scope of VIEWS beyond regional haze Tasks: Collaborate with the EPA to define requirements, tasks, and output products Import the raw hourly ozone data into the VIEWS integrated database Determine the desired aggregations and subsets of the data to provide Design the end user output products and tools for exploring and analyzing the data EPA Ozone and Multiple Pollutant Project

6. EPA Data Summit (RTP): Convened groups with key roles in managing, analyzing, and disseminating earth observation data in order to explore efficient means of leveraging existing efforts Explored mechanisms and potential opportunities for “interoperability” between systems Assisted EPA/OAQPS in honing its role in the larger earth observation community Established a community-wide strategy for responding to user-defined needs EPA Data Summit link: http://wiki.esipfed.org/index.php/Data_Summit_Workspacehttp://wiki.esipfed.org/index.php/Data_Summit_Workspace Earth Science Information Partners (ESIP) Federation Collaborate on interoperability efforts for data/metadata discovery and exchange Contribute data and services to the Earth Information Exchange ESIP website: http://www.esipfed.org/http://www.esipfed.org/ GEO/GEOSS Architecture Implementation Pilot (AIP) 2 Contribute components and services to the GEOSS registry Participate in efforts to standardize and streamline data discovery and exchange Develop VIEWS/TSS as an “persistent operational exemplar” of the GEOSS architecture GEOSS AIP 2 link: http://www.ogcnetwork.net/AIpilothttp://www.ogcnetwork.net/AIpilot Collaborations and Community Activities

7. “Interoperability”: The ability of diverse systems and organizations to work together to exchange and utilize information. To facilitate this, VIEWS will offer the following services and features:  Discovery, retrieval, and exchange of data and metadata  On-the-fly transformation and formatting of data and metadata  Upload and management of user-supplied data and metadata  Generation of visualization and analysis products  Availability of “embeddable” components and tools  Support of OGC web standards for spatial data exchange VIEWS Interoperability: Services and standards

8. WRAP FETS: Incoming prescribed fire data via a co-located database WRAP EDMS: Incoming WRAP emissions inventories WRAP Regional Modeling Center (RMC): Incoming modeled emissions data; necessary for chemical transport modeling data, modeling data results, and gridded emissions inventories that cannot be obtained elsewhere AQS: Outgoing IMPROVE data, incoming PM2.5, PM10, Ozone, etc AirQuest: Incoming satellite data; other datasets being considered AirNow: Incoming Air Quality Index maps and ozone data DataFed: Outgoing IMPROVE data via direct ODBC connection to the VIEWS database; various incoming datasets RSIG: Incoming satellite data and products (future) Giovanni: Incoming satellite data and products NASA DAACs: Incoming satellite data and products BlueSky Framework: Pending proposal; Hybrid source apportionment model to be provided by NPS to BlueSky through web services VIEWS Interoperability: Connected systems

9. Leveraging the VIEWS Architecture

10. First question we ask ourselves when designing a new feature: “Can its design be generalized for VIEWS while providing for customization and domain-specific use by connected systems?” If “yes”, then the benefits are: Project and configuration management are simplified Dependent systems can be more “lightweight” The system as a whole can be extended more easily Past and current investments are leveraged and maximized Interoperability and data sharing with external systems is made easier Developers can “implement once, reuse often” Collaboration is facilitated and expedited Leveraging the VIEWS Architecture (cont’d)

11. John Huddleston Design and development System administration Data acquisition and management Duli Chand Data analysis Scientific research Design of visualization and analysis features Additions to the VIEWS team

12. Database server: 2.5 – 5 Terabytes of storage; data storage, transformation, and access Web server: Pages, services, and tools File server: Documents, images, photos GIS Server: ESRI suite of tools, static base map collection Processing Server: IDL operations, contour maps, intensive processing Relocation to dedicated server room Overall, ongoing goal: Leverage resources and facilities already available from CIRA Updated hardware infrastructure

13. New VIEWS website The new website has been in development for approximately 24 months The first official launch is planned for the latter part of Q2 2009 Additional updates and additions are planned throughout 2009 as part of a progressive roll-out Introduces a new look-and-feel, layout, and navigation scheme Incorporates new web technologies, design principles, and performance optimizations Adds a “developer center” that contains instructions and guidelines for using VIEWS web services and embeddable components Integrates the user registration and authentication infrastructure for VIEWS, TSS, ATDA, and other VIEWS systems Uses Google Analytics for website traffic and usage statistics Incorporates Google Maps into key tools Provides context-sensitive tooltips and “hot links” that are integrated with the VIEWS glossary

14. New VIEWS website (cont’d) Provides an updated version of the Database Query Wizard that allows the user to obtain much more than just raw data Introduces a “Dataset Catalog” that facilitates the browsing, searching, and exploration of VIEWS datasets Offers an updated Metadata Browser that uses Google Maps for exploring monitoring site metadata Introduces dynamic Air Quality Index (AQI) maps via real-time retrieval from the AirNow website Provides an improved webcams page that is better organized and allows for searching and sorting Adds a large Glossary of Terms that allows for quick browsing and mouse- over tooltips throughout the website Introduces a “Rosetta Stone” for comparing and cross-referencing parameter definitions across different datasets Links IMPROVE data advisories to relevant data products Links exceptional event metadata to relevant data products

15. Work with UCD to decrease the time lag for disseminating IMPROVE datasets Goal for routine data updates: No more than a 3 month lag between data availability and public dissemination Goal for RHR datasets: No more than a 4 month lag between routine IMPROVE data dissemination and RHR data dissemination Increase the efficiency of preliminary IMPROVE data review: Consider creating an online review and approval tool for expediting the review process Import other datasets on a more frequent, up-to-date basis Work with partners in the air quality community to create more uniform flags, codes, and descriptions for data and metadata Offer future data products as web services and re-factor existing products as web services Offer metadata management tools for program and site managers Future goals and plans

16. Continue participating in community interoperability efforts Establish long term data exchange mechanisms with connected systems Implement an online forum for questions, comments, discussions, and news Expand the scope of the “Air Data Wiki”: http://vista.cira.colostate.edu/airdatawikihttp://vista.cira.colostate.edu/airdatawiki Participate in two potential NASA ROSES projects: Exceptional Event Decision Support System (Rudy Husar) Make monitoring data available online and via web services Participate in event analyses Assist with the development of decision support tools NAAPS Products for Air Quality Decision-making (Doug Westphal) Discovery, display, analysis, and retrieval of NAAPS data Future goals and plans (cont’d)

17. New and updated VIEWS tools Query WizardDataset IndexMetadata Browser AirNow AQI MapsWebcams PageGlossary

18. New Query Wizard and Mouse-over Help

19. New Metadata Browser Google Maps used for showing site locations Site photos Site details and history Tabular site list for sorting and quick selection

20. Glossary And Codes Key Glossary entries show up as tooltips whenever they’re used in web pages. Jump to beginning letters.

21. “Rosetta Stone” for Dataset Parameters

22. Exceptional event metadata (such as fires) is stored and dynamically associated with data at run time in order to better inform the user about the context of the data. “Bisquit” fire impacting Crater Lake in 2002 Exceptional Event Metadata

23. IMPROVE Data Advisories document interesting findings from the IMPROVE database such as data anomalies, potential problems, and new uses for the IMPROVE data. These advisories are stored as metadata in the VIEWS database and dynamically associated with data and products. When a user selects data, the systems checks for any advisories relevant to the data selected and attaches them to the output. IMPROVE Data Advisories