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Published byGwenda Hardy Modified over 9 years ago
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Preserving the Comparability of Sensor Data A Possible Use Case Charles S. Spooner, US EPA ESIP 2010 Winter Meeting Washington, DC
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Water Quality Data ► Overwhelmingly an investment by public agencies ► Our goal is to preserve that investment for future use recognizing that: the value of good data increases over time the value of undocumented data decreases quickly
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Data Comparability ► Reliability and confidence in long-term, broad scale datasets is directly related to maintenance of data quality, and the ability of the scientific community to summarize and communicate that confidence (Costansa et al., 1992; Edwards, 2004) ► Comparability is defined by EPA’s Quality Assurance Division as “the confidence that two data sets can contribute to a common analysis and interpolation” (USEPA, 2006).
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Comparable Water Quality Data ► Minimum Metadata to travel with the data The standard data elements of the Advisory Committee on Water Information (ACWI) ► Chemical & Microbiological Analytes ► Toxicity ► Population and Community Level Analytes ► Physical Habitat Characterizations EPA Environmental Sampling, Analysis and Results Standards (ESAR) EPA/USGS Water Quality Exchange Schema (WQX)
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Sensors: Defining Water Quality in the Future ► Continuous data – More relevant ► Real-time data - Immediate access ► Better/Different coverage More relatable to watershed and weather data
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Comparable Sensor Water Quality Data ► Continuous data, not discrete samples ► Current practices Influenced by non-standard vendor software Applied in research settings Being driven by a search for a language that can promote data transmission ► Water ML ► Sensor ML
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The Basic Issues ► Will These MLs Protect the Comparability of Sensor Data ? ► How will the data be stored?
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Examples of Sensor Deployments These examples are from the Chesapeake Bay where This use case might easily be focused
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DataFlow Aboard Ship
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Automous Underwater Vehicle
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Gliders
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Gliders
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Vertical Profilers
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Proposed Use Case ► Compare metadata fields for 1.Existing WQ sensors in different settings ► Vertical profilers ► Data Flow systems ► Autonomous Underwater Vehicles 2.The WQX Schema 3.Sensor Workgroup Data Elements – AQ, Calibration, Operator Competence 4.Water ML 5.Sensor ML
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Use Case Results
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