Essay on "Origins and Applications of the Guide to the Expression of Uncertainty in Measurement Gum"

Essay 5 pages (1671 words) Sources: 5 Style: Harvard

[EXCERPT] . . . .

GUM

Origins and applications of the Guide to the Expression of Uncertainty in Measurement (GUM).

The Guide to the Expression of Uncertainty in Measurement commonly known as GUM is a document produced by the Joint Commission for the Guides in Meteorology (JCGM). The work demonstrates a standardized manner of recording, for comparison measurement uncertainty, with the initial focus on meteorology (JCGM 2011). Measurement uncertainty itself can be a troubling issue derived from many sources; environmental, instrument sourced, user variations and the actual item being measured, and it exists to some degree in potential in nearly every measurement (Bell 1999, p. 7). The idea associated with GUM is that the true measurement cannot be expressed without the inclusion of the variation or uncertainty of that measure and that there should be a standardized (comparable) way in which this is expressed. According to the International Organization of Standardization (one of the members of the JCGM) the application of GUM extends across many areas of interest including:

maintaining quality control and quality assurance in production; complying with and enforcing laws and regulations; conducting basic research, and applied research and development, in science and engineering; calibrating standards and instruments and performing tests throughout a national measurement system in order to achieve traceability to national standards; developing, maintaining, and comparing international and national physical reference standards, including reference materials. (ISO 2011)

The guide itself is rather complicated by most standards, but offers a set of rules that demonstrate standardization that has not been seen prior to its publication, allowing measurements to be compared in ways previously not possible and new data sets and calculations to result from it, as well as greater understandings of that which is being measured. To some degree the importance of this is that it has an international application and individuals and/or organizations with substantial barriers can communicate in a common language, understanding and comparing measures that were previously unexplored and/or considered untrustworthy based on parameters of unknown uncertainties and limitations in the known level of certainty that the uncertainties express (JCGM 2008). The first inception of GUM came about in 1993, after years of development by various groups of the joint commission but its most recent publication/revision is from 2008 and available freely in electronic format.

With the publication of the GUM and its widespread dissemination, problems associated with inconsistent approaches to uncertainty evaluation are lessening (or at least are less obvious). The main practical test of uncertainty methodologies is made through interlaboratory comparisons in which one or more travelling standards are measured by a number of laboratories and their results compared… (Cox, Forbes & Harris 2004, p. 85).

Though GUM is not the only available format for producing uncertainties calculations it is probably the most widely recognized and the most commonly used process.

Though the initial intent of creating transferable and comparable meteorological data has been expanded to a multiuse platform one of the most important and growing aspects of the original intent, meteorological standardization is though the development of the environmental sciences, and especially in tracking climate change. Climate change is a relatively new area of focus in meteorology but one that has enraptured the population of the earth and in many ways created a sense of collective (international) responsibility for both monitoring environmental measures and formulating reason and collective action as a result. The result is that the various agencies, civil and private that monitor and track change in the environment on a global scale must be able to more easily interpret and theorize on data coming from multiple sources in every location on the globe. Therefore the application of GUM has been widely accepted in this area of research as a tool that allows various scientists the ability to compile, compare and deal with vast amounts of data in a similar way and trust their measurements and those of others to a greater degree. Some examples this researcher found associated with this phenomena are telling of the trend.

The first example comes from a piece of peer reviewed literature in the International Journal of Remote Sensing where the researchers begin by explaining that the science of remote sensing requires the compilation of millions of measurements from all over the world. "A major challenge for the international remote sensing community is to provide data that can be used to monitor climate change and to quantify changes whether natural or human induced," (Datla, Kessel, Smith, Kacker, & Pollock 2010, p. 868). The researchers then go on to state that they use GUM as a means of creating data that is comparable and reliable across many locations and that allows for variations in the locations and numbers of collection measures at any given time (870). The work even states the development of their own methodology for research based on the GUM principles:

We propose a methodology based on the International Organization for Standardization (ISO) Guide to the Expression of Uncertainty in Measurement (GUM) for the analysis of uncertainties in such measurements along with consistency checking. This allows the measurement result and its associated uncertainty to evolve as new knowledge is gained from additional experiments, and it promotes greater caution in drawing conclusions in view of the sparse measurements. We use data from ongoing total solar irradiance measurements from various instruments in orbit to illustrate the principles…(Datla, Kessel, Smith, Kacker, & Pollock 2010, p. 867).

To some degree the point of such a movement in any science would be to create a system that is so universally utilized that years of data from this pint forward are expressed in so much the same way that they can be statistically compared to show trend and change as effectively as possible.

An additional example in the literature includes an article discussing the standardization of the measurements of Beryllium in air filter samples. The focus of this research is much more finite, still having to do with environmental science but showing the variation of application with regard to Gum. In the first example the methodology of GUM was used to determine statistical standardization in uncertainty treatment for a large data set with a multitude of measurements, while this particular example demonstrates its use as a way to universalize the measurement of a particular and particularly troubling element in the air, in this case in workplace samples (Ashley, Brisson, Howe & Bartley 2009). The variations of scope and scale between these two applications of GUM are particularly interesting as they demonstrate a significant level of infiltration of the desire of the scientific community to standardize many aspects of their work so it can be applied across various levels and can be understood by many more interested parties. As in the former example the two sets of researchers are fundamentally focused on applying GUM to create a Common Reference Value (CRV) that applies universally to the uncertainty of measures so that any interested party can mathematically compare data and understand its value in the scope and scale of measurements.

Applications for GUM in the environmental sciences are relatively limitless and the same can be said about other areas of scientific measure. Creating CRVs is one particular area where GUM will likely be even more widely utilized and adopted, across science to allow scientists all over the world to access data and create larger comparable data sets to better understand trends and change in climate as well as manmade alterations in the environment. Given that the environmental sciences focus on climate change has become an almost exponential area of study over the last 30 years the applications will likely be seen across the board as more and more interested organizations and nations see the wisdom in sharing data and being able to view and trust the data of other gathering agencies.

One rather intriguing emerging trend… READ MORE

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