NUSAP

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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]

Contents

The concept

The name "NUSAP" is an acronym for the categories just mentioned.

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. Recent applications of NUSAP are in the field of climate science, [3] [4] hydrology, [5] medical research [6] and risk assessment. [7] [8] Applications relevant to the activities of the European Food Safety Authority EFSA are Bouwknegt and Havelaar (2015) [9] and EFSA BIOHAZ Panel, (2015). [10]

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. [11] [12] [13]

An early description of NUSAP is due to Funtowicz and Ravetz. [14]

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<span class="mw-page-title-main">Post-normal science</span> Approach to the use of science on urgent issues involving uncertainty in facts and moral values

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<span class="mw-page-title-main">Jerome Ravetz</span> American philosopher

Jerome (Jerry) Ravetz is a philosopher of science. He is best known for his books analysing scientific knowledge from a social and ethical perspective, focussing on issues of quality. He is the co-author of the NUSAP notational system and of Post-normal science. He is currently an Associate Fellow at the Institute for Science, Innovation and Society, University of Oxford.

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<i>Uncertainty and Quality in Science for Policy</i>

Uncertainty and Quality in Science for Policy is a 1990 book by Silvio Funtowicz and Jerome Ravetz, in which the authors explain the notational system NUSAP and applies it to several examples from the environmental sciences. The work is considered foundational to the development of post-normal science.

<span class="mw-page-title-main">Silvio Funtowicz</span> Philosopher of science

Silvio O. Funtowicz is a philosopher of science active in the field of science and technology studies. He created the NUSAP, a notational system for characterising uncertainty and quality in quantitative expressions, and together with Jerome R. Ravetz he introduced the concept of post-normal science. He is currently a guest researcher at the Centre for the Study of the Sciences and the Humanities (SVT), University of Bergen (Norway).

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<span class="mw-page-title-main">Andrea Saltelli</span> Italian researcher (born 1953)

Andrea Saltelli is an Italian scholar specializing in quantification using statistical and sociological tools. He has extended the theory of sensitivity analysis to sensitivity auditing, focusing on physical chemistry, environmental statistics, impact assessment and science for policy. He is currently Counsellor at the UPF Barcelona School of Management.

The concept of Extended peer community belongs to the field of Sociology of science, and in particular the use of science in the solution of social, political or ecological problems. It was first introduced by in the 1990s by Silvio Funtowicz and Jerome R. Ravetz. in the context of what would become Post-normal science. An Extended peer community is intended by these authors as a space where both credentialed experts from different disciplines and lay stakeholders can discuss and deliberate.

References

  1. Funtowicz, S. & Ravetz J., 1990, Uncertainty and Quality in Science for Policy, Kluwer Academic Publishers, Dordrecht.
  2. 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.
  3. 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.
  4. Lorenz, S; Dessai, S; Paavola, J; Forster, P M., 2015, The communication of physical science uncertainty in European National Adaptation Strategies, Climatic Change132.1 (Sep 2015): 143-155.
  5. Zhu, Q., Xu, X., Gao, C., Ran, Q.-H., Xu, Y.-P., 2013, Qualitative and quantitative uncertainties in regional rainfall frequency analysis, Journal of Zhejiang University: Science A, Volume 16, Issue 3, 2015, Pages 194-203.
  6. Kloprogge, P., Van der Sluijs, J.P., Petersen, A.C., 2011, A method for the analysis of assumptions in model-based environmental assessments, Environmental Modelling and Software, 26(3), 289-301.
  7. Ides Boone, Yves Van der Stede, Jeroen Dewulf, Winy Messens, Marc Aerts, Georges Daube and Koen Mintiens, 2010, NUSAP: a method to evaluate the quality of assumptions in quantitative microbial risk assessment, Journal of Risk Research, 13(3), 337-352.
  8. Christine Louise Berner, Roger Flage, 2016, Comparing and integrating the NUSAP notational scheme with an uncertainty based risk perspective, Reliability Engineering & System Safety, 156, Pages 185–194.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. Funtowicz, S. O. & Ravetz, J. R. 1993. Science for the post-normal age. Futures, 25(7), 739–755.
  14. S. 0. Funtowicz and J.R. Ravetz, 1992, Uncertainty and Quality in Science for Policy, Radical Statistics, 50 (Spring '92), 31-34.