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

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Presentation transcript:

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

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.

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.

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.

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.

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.

Data Value Chain Diagram

To build FED, we started with VIEWS…

…and developed a distinct identity based upon an established base

Online Suite of Data Access and Visualization Tools

Interactive Data Explorer: Dataset View

Interactive Data Explorer: Park View

Spatial Display and Analysis Tool

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 Current Objectives and Plans

Thanks.

Primary Goal: Integrated Air Quality Decision Support Decisions (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)