NUSAP
NUSAP is a notational system for the management and communication of uncertainty in science for policy, based on five categories for characterizing any quantitative statement: Numeral, Unit, Spread, Assessment and Pedigree. NUSAP was introduced by Silvio Funtowicz and Jerome Ravetz in the 1990 book Uncertainty and quality in science for policy.[1] See also van der Sluijs et al. 2005.[2]
The concept
The name "NUSAP" is an acronym for the categories just mentioned.
- Numeral will usually be an ordinary number;
- Unit refers to the units used in Numeral
- Spread is an assessment of the error in the value of the Numeral.
- Assessment is a summary of salient qualitative judgements about the information - this can be of statistical nature (a significance level) or more general, e.g. involving terms such as 'conservative' or 'optimistic'.
- Pedigree is an evaluative description of the mode of production and of anticipated use of the information.
The pedigree can be expressed by means of a matrix; the columns represent the various phases of production or use of the information, and each column contains marks to rank the performance. Marks can be numerical as well as qualitative, see an example here. See recent applications [3] .[4] Applications relevant to the activities of the European Food Safety Authority EFSA are Bouwknegt and Havelaar (2015)[5] and EFSA BIOHAZ Panel, (2015)[6].
Together with Sensitivity auditing NUSAP can be considered as a method useful at the science policy interface - when numbers produced by either experiment, survey or mathematical modelling need to be used in the appraisal or the formulation of a policy. See also Post-normal science [7] [8] .[9]
An early description of NUSAP due to Funtowicz and Ravetz [10] is here.
External links
- The web page of NUSAP maintained by Jeroen van der Sluijs, Universities of Utrech (NL) and Bergen (NO).
- NUSAP – philosophical background, by Jerome R. Ravetz .
References
- ↑ Funtowicz, S. & Ravetz J., 1990, Uncertainty and quality in science for policy, Kluwer Academic Publishers, Dordrecht.
- ↑ van der Sluijs, J., Craye, M., Funtowicz, S., Kloprogge, P., Ravetz, J., and Risbey, J. (2005) Combining Quantitative and Qualitative Measures of Uncertainty in Model based Environmental Assessment: the NUSAP System, Risk Analysis, 25 (2). p. 481-492.
- ↑ Van Der Sluijs, J.P., Wardekker, J.A., 2015, Critical appraisal of assumptions in chains of model calculations used to project local climate impacts for adaptation decision support - The case of Baakse Beek, Environmental Research Letters, 10(4), doi:10.1088/1748-9326/10/4/045005.
- ↑ Kloprogge, P. , Van der Sluijs, J.P. , Petersen, A.C., 20122, A method for the analysis of assumptions in model-based environmental assessments, Environmental Modelling and Software, 26(3), 289-301.
- ↑ Bouwknegt M and Havelaar AH, 2015. Uncertainty assessment using the NUSAP approach: a case study on the EFoNAO tool. EFSA supporting publication 2015: EN-663, 20 pp.
- ↑ EFSA BIOHAZ Panel (EFSA Panel on Biological Hazards), 2015. Scientific Opinion on the development of a risk ranking toolbox for the EFSA BIOHAZ Panel. EFSA Journal 2015;13(1):3939, 131 pp. doi:10.2903/j.efsa.2015.3939.
- ↑ Funtowicz, S.O. and Jerome R. Ravetz (1991). "A New Scientific Methodology for Global Environmental Issues." In Ecological Economics: The Science and Management of Sustainability. Ed. Robert Costanza. New York: Columbia University Press: 137–152.
- ↑ Funtowicz, S. O., & Ravetz, J. R. 1992. Three types of risk assessment and the emergence of postnormal science. In S. Krimsky & D. Golding (Eds.), Social theories of risk (pp. 251–273). Westport, CT: Greenwood.
- ↑ Funtowicz, S. O. & Ravetz, J. R. 1993. Science for the post-normal age. Futures, 25(7), 739–755.
- ↑ S. 0. Funtowicz and J.R. Ravetz, 1992, Uncertainty and quality in science for policy, Radical Statistics, 50 (Spring '92), 31-34.