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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Presentation transcript:

Preserving the Comparability of Sensor Data A Possible Use Case Charles S. Spooner, US EPA ESIP 2010 Winter Meeting Washington, DC

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

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).

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)

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

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

The Basic Issues ► Will These MLs Protect the Comparability of Sensor Data ? ► How will the data be stored?

Examples of Sensor Deployments These examples are from the Chesapeake Bay where This use case might easily be focused

DataFlow Aboard Ship

Automous Underwater Vehicle

Gliders

Gliders

Vertical Profilers

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

Use Case Results