Making Good Decisions About Using Environmental Data. K. M. Morgan and M. J. Bertoni, Research Triangle Institute
Environmental risk assessors may find themselves either with an over-abundance of data to sort through or with only a few small sets of data on which to base their conclusions. Statisticians and decision analysts have developed many different methodologies and approaches for how to use data to make decisions, but it is not always clear how decision-makers should incorporate information about the quality of the data that they are using. Quality assurance and quality control methodologies are designed to characterize data as being of differing quality for any particular decision. For example, laboratories and other generators of data attach "data flags" to their data to indicate the quality of the data. Data of differing quality should be treated differently in terms of what it adds to the quality of the decisions. The mapping of data quality to decision quality may not be well understood by data users - they may assume that if the data is of good enough quality to be used, that it is all the same. This issue is becoming even more important as the use of secondary data (data that was generated by another project) is increasing due to interest in reducing costs and the need for increased efficiency. Also relevant are the proliferation of GIS-based data tools, which by putting data in a picture format, make it seem more "true." This talk will discuss research to develop a framework for describing and evaluating the effect of data quality on decision quality, in a way that is operationally tractable for decision makers.
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