Free ENBIS Webinar on Measurement Systems Analysis for Distributed Measurement Systems: Using Sensor Networks in Environmental and Climate Monitoring15 January 2015; 12:45 – 13:30; Webinar
Alistair Forbes will talk about measurement systems and process improvement. The webinar will be moderated by Jacqueline Asscher.
The primary role of National Metrology Institutes such as the National Physical Laboratory, UK, is to ensure that measurements made at any time and any place are comparable and traceable to the same standard units, e.g., those defined by the System International (SI). The International Vocabulary of Metrology (VIM) defines traceability as the “property of a measurement result whereby the result can be related to a reference through a documented unbroken chain of calibrations, each contributing to the measurement uncertainty”. The current metrology paradigm of standards, calibration and traceability is designed for the measurement of a single quantity using a single, dedicated measuring instrument or system, e.g., measuring the length of an artefact using a laser interferometer. However, much of environmental monitoring, for example, necessarily involves networks of sensors measuring a number of different quantities at several locations and at different times, generating a large amount of data. Whether the characteristic being measured is an air pollutant level, acoustic noise, or sea water salinity, etc., measurements at particular spatial and time locations are transformed, via data analysis algorithms, to make inferences at other individual spatial and time locations or are aggregated to make inferences over a region or time period. If the outputs of the data transformation process are to be considered traceable to standard units, then we need to be able to associate uncertainties with these outputs and demonstrate that these uncertainty statements can be relied upon.
This webinar will discuss:
- Current metrology infrastructure and uncertainty evaluation methodologies
- Challenges in extending those methodologies to sensor networks, in particular looking at issues associated with data provenance, metadata, and model uncertainty
- The Big Data agenda
This is an area where the statistical community has a major role in helping metrologists address these challenges.