1. Federal Land Manager Environmental Database (FED)
Overview and Update
June 6, 2011
Shawn McClure

3. Observed Data Modeled Data Reported Data Multidimensional Data Fusion
Data Fusion: Integrating data from multiple sources to achieve inferences, which will be more efficient and potentially more accurate than if they were achieved by means of a single source.

4. Database Website Software Integrated, Service-Oriented Architecture
SOA: A flexible set of design principles for systems development that enables the packaging of functionality as a suite of interoperable services that can be used across multiple, separate systems that exist in various application domains.

5. Knowledge Infrastructure Applications Functional Domain Integration
Functional Domain Integration: Enabling the integration of functionality and benefits from generalized domains of expertise in order to add value to systems that address more specific problem domains, such as air quality.

6. Assessment Analysis Decisions Value-Added Outcomes
Value-Added Outcomes: Benefits and results that are useful and actionable in terms of addressing air quality issues across time, space, organizational boundaries, and perspectives.

7. Architected Air Quality Decision Support
Overall Goal: The synthesis of multiple, diverse components into an integrated, online environment in order to manage complexity, facilitate analysis, and enable decisions.

8. Data Value Chain Diagram

9. To build FED, we started with VIEWS…

10. …and developed a distinct identity based upon an established base

11. Online Suite of Data Access and Visualization Tools

12. Interactive Data Explorer: Dataset View

13. Interactive Data Explorer: Park View

14. Spatial Display and Analysis Tool

15. Focus on monitored data Facilitate easier data integration
Current Objectives and Plans
Focus on monitored data
Facilitate easier data integration
Achieve a high degree of data availability
Enable quick and accurate assessments of air quality
Design a more park-centric user interface
Support Regional Haze Rule data needs and analyses
Provide a fluid process for generating ozone metrics
Facilitate NPS air quality modeling efforts
Integrate Night Skies imagery and data
Develop interoperability with other data systems

16. Thanks.

20. Primary Goal: Integrated Air Quality Decision Support
(interpretations, conclusions, guidelines, regulations
Science
(knowledge, examples,
expertise, theory)
Analysis
(Tools, reanalysis, modeling,
inputs from other systems)
Processed data
(calculated, RHR,
normalized, value-added)
Raw data
(observations, methods)