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Darone Jones - Program Lead Aaron Sutula – Technical Lead

Darone Jones - Program Lead Aaron Sutula – Technical Lead. Iris Application Framework. Field Motivation. Field needs an advanced set of integrated Decision Support Service (DSS) tools Situational awareness beyond current capabilities of AWIPS

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Darone Jones - Program Lead Aaron Sutula – Technical Lead

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  1. Darone Jones - Program Lead Aaron Sutula – Technical Lead Iris Application Framework

  2. Field Motivation • Field needs an advanced set of integrated Decision Support Service (DSS) tools • Situational awareness beyond current capabilities of AWIPS • Event logging/storm reporting • Cataloging of impacts/concerns • Contact management (spotters, EM, etc.) • Sharing of local office DSS data to assist in service backup • Mapping data interface – common application to display all data • Field needs a single framework for future field innovation efforts

  3. Iris Motivation • Build Data Compatibility / Build DSS Solutions • Central collection and distribution point for many types of data • Replace multitude of programs, databases, and data formats with a single structure and location where this information is stored and retrieved • Facilitate sharing of information between offices, programs, regional and national headquarters • Provide common interface from which forecasters can easily determine if forecast weather will have an impact on particular NWS stakeholders

  4. What is Iris? • A database and application framework engineered to manage many types of NWS data: • customer contact information, criteria and thresholds, spotter information, communication logs, equipment status, office/community events, weather events and storm reports, NWS products, and verification • Hazard products broken down and stored in their atomic parts Development being done with industry standards AND consistent with AWIPS Extended technologies

  5. Background • Grew from field efforts to address DSS needs; each application using similar data • StormLog (spotter management / report logging) • PANDA (verification) • SevereClear (situational awareness) • Various spreadsheets / contact management • Each application required its own database and decoders • Info entered multiple times; hard to manage or share, duplication of effort • Group of field/regional staff banded together and engineered concept of single database structure for all applications • Often without easy ways to support backup modes

  6. Architecture Web Client Qooxdoo IrisCore Database Postgres + PostGIS Persistence Hibernate Spring RPC JabsorbAPI Other Clients

  7. BackgroundContinued • Iris team developed current goals/structure/framework • Sought out and conducted own training on technologies • Field/Regional staff developing in spare time • ITOs, SOOs, WCMs, Forecasters, Program Mgrs • Using patch work equipment • Progress has been good...given part-time aspect • IAB/RITT/OS&T funded 2 developer workshops (January 2010, August 2010)

  8. Database • PostgreSQL • PostGIS extensions • Contains pre-populated quality controlled NWS and General GIS data (states, counties, NWS zones, etc.)

  9. Major Data and Design Elements • All data modeled in POJO (Plain Old Java Objects) • Javascript mapping is to standard (JSON and GeoJSON) • Using industry standards and conventions • Spring, Hibernate, PostGIS, Maven, Agile development • Store existing NWS products in Spatial database • Correlation of Spatially related data

  10. Distributed Development • NWSChat • GoToMeeting • Bi-weekly conf calls • Planning and code sprint meetings

  11. Iris WebClient Applications • Initial phase: implement 4 DSS applications – Iris Web: • Next Generation Local Storm Report (LSR) Program • Contact Management • Impacts Catalog • Situational awareness display • All using a single database and client application framework • Allows for ease of local data sharing, especially for service backup situations

  12. Long-Term Goals – NWS Use of IrisBe the standard database framework for all NWS weather operations (consolidate systems/databases) “Achieving the NextGen weather vision will require increased compatibility among NOAA systems (e.g., through common data standards and formats), the enterprise infrastructure to link the systems to one another, and intensified cooperation among the NOAA system owners.” Build compatibility

  13. Potential NOAA Collaborations • Recent environmental issues have shown the value of cross-agency collaboration (Katrina and Ike, Deepwater, Kalamazoo) • Provide documentation on available data • Planned NWS API • Sharing of data in standard formats • GIS • WMS, WFS, KML, etc. • CAP, RSS, etc. • We’d love to learn about what data is available from you • NWSChat • Wiki/Sites – Team(s) • Potential future collaboration on application development

  14. Questions Darone.Jones@noaa.gov Aaron.Sutula@noaa.gov

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