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Federal Land Manager Environmental Database (FED)
Overview and Update June 6, 2011 Shawn McClure
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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.
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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.
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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.
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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.
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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.
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Data Value Chain Diagram
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To build FED, we started with VIEWS…
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…and developed a distinct identity based upon an established base
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Online Suite of Data Access and Visualization Tools
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Interactive Data Explorer: Dataset View
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Interactive Data Explorer: Park View
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Spatial Display and Analysis Tool
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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
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Thanks.
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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)
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