Abstract
This chapter deals with traceability and comparability: the first of the two major hallmarks of metrology (quality-assured measurement). (The second hallmark—uncertainty—is covered in the final chapters of the book.)
Metrological traceability through calibration enables the measurement comparability needed, in one form or another, to ensure entity comparability in any of the many fields mentioned in the first lines of Chap. 1. The “Zanzibar” parable, illustrating the concept of measurement comparability, recalled in this chapter, captures the essence of the concept of trueness, that is, what defines being “on target” when making repeated measurements in the “bull’s eye” illustration of measurement accuracy. Examples of circular traceability in measurement are more common than one would hope.
Despite its importance, international consensus about traceability of measurement results—both conceptually and in implementation—has yet to be achieved in every field. Ever-increasing demands for comparability of measurement results needed for sustainable development in the widest sense require a common understanding of the basic concepts of traceability of measurement results at the global level, in both traditional and new areas of technology and societal concern.
The present chapter attempts to reach such a consensus by considering in depth the concept of traceability, in terms of calibration, measurement units and standards (etalons), symmetry, conservation laws and entropy, in a presentation founded on quantity calculus. While historically Physics has been the main arena in which these concepts have been developed, it is now timely to take a broader view encompassing even the social sciences, guided by philosophical considerations and even politics. At the same time as the International System of Units is under revision, with more emphasis on the fundamental constants of Physics in the various unit definitions, there is some fundamental re-appraisal needed to extend traceability to cover even the less quantitative properties typical of measurement in the social sciences and elsewhere.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
German: ’Sachgrösse = Objektgrösse (mit Objektbindung behaftete Grösse). Sie hat Quantität, die aber unbestimmt bleibt, sie hat Sachbezug (Objektbezug)’ Fleischmann (1960).
- 2.
Chapter 5 contains a description of how to test these assumptions.
- 3.
Note however that there is no explicit reference in Eq. (3.2) to which object/entity is being measured, but rather to a certain kind of quantity.
- 4.
This assumes of course that the necessary separation of object and instrument can be performed for the measurement system at hand (Sect. 3.1.2).
- 5.
Calibration hierarchy: ‘sequence of calibrations from a reference to the final measuring system, where the outcome of each calibration depends on the outcome of the previous calibration’ [VIM §2.40].
- 6.
‘Definitional uncertainty’—‘resulting from the finite amount of detail in the definition of a measurand’ [VIM 2.27]—is of course in most cases much smaller in the strong objectivity of physics than in the social sciences.
- 7.
‘That is, a definition in which the unit is defined indirectly by specifying explicitly an exact value for a well-recognized fundamental constant’ [24th CGPM, 2011 On the possible future revision of the International System of Units, the SI (CR, 532), Resolution 1].
- 8.
By the correspondence principle, relations specific to quantum mechanical effects, e.g. on the microscopic scale, can find correspondence to relations in Newtonian physics, e.g. at the macroscopic scale where the Planck constant is negligibly small.
- 9.
The Planck constant is not merely a ‘number’ but has multiplicity of roles, such as (1) a constant of proportionality between canonical pairs of quantities (e.g. energy/time, momentum/position, angular momentum/rotation); (2) acting as a fundamental unit as the ‘quantum’ of ’action’ (e.g. energy·time); (3) is implicit in many of the ‘quantum’ definitions of the SI, not only the kilogram but also the second, volt and ohm; (4) quantifying the interaction through fields between physical systems, such as the electromagnetic interaction mediated by ‘virtual’ photons (Cohen-Tanoudji 1993).
References
J. Aitchison, The statistical analysis of compositional data. J. R. Stat. Soc. 44, 139–177 (1982)
A. Asril and I. Marais, (2011) Applying a Rasch Model Distractor Analysis. In: Cavanagh R.F., Waugh R.F. (eds) Applications of Rasch Measurement in Learning Environments Research. Advances in Learning Environments Research, vol 2. SensePublishers, Rotterdam
S. Barbic and S. Cano, The application of Rasch measurement theory to psychiatric clinical outcomes research, BJPsych Bulletin, 40, 243–244, https://doi.org/10.1192/pb.bp.115.052290 (2016)
F. Attneave, Informational aspects of visual perception. Psychol. Rev. 61, 183–193 (1954)
H. Barlow, The exploitation of regularities in the environment by the brain. Behav. Brain Sci. 24, 602–607 (2001)
J. Barrow, From Alpha to Omega (Jonathan Cape, London, 2002). ISBN 0224061356
E. Bashkansky, S. Dror, R. Ravid, P. Grabov, Effectiveness of a product quality classifier. Qual. Eng. 19(3), 235–244 (2007)
J.P. Bentley, Principles of Measurement Systems, 4th edn. (Pearson, Prentice-Hall, Lebanon, 2004). ISBN-13: 978-0130430281, ISBN-10: 0130430285
BIPM, On the Future Revision of the SI, (2018), https://www.bipm.org/en/measurement-units/rev-si/
M. Born, Atomic Physics, 8th edn. (Blackie & Son Ltd., London, 1972). 216.89027.6, ISBN-13: 978-0486659848, ISBN-10: 0486659844
N.R. Campbell, Physics – The Elements (Cambridge University Press, Cambridge, 1920)
CGPM, SI Brochure: The International System of Units (SI), 9th edn. (2019), https://www.bipm. org/utils/common/pdf/si-brochure/SI-Brochure-9.pdf
CGPM, On the revision of the International System of Units (SI), in Draft Resolution A – 26th meeting of the CGPM (13–16 November 2018), (2018), https://www.bipm.org/utils/en/pdf/CGPM/Draft-Resolution-A-EN.pdf
CODATA, Task Force on Fundamental Physical Constants, Committee on Data for Science and Technology (ICSU, Paris, 2004). http://www.codata.org/taskgroups/TGfundconst/index.html
G. Cohen-Tannoudji, Universal Constants in Physics (MCGRAW HILL HORIZONS OF SCIENCE SERIES), ISBN-13: 978-0070116511, McGraw-Hill Ryerson, Limited (1993)
P. de Bièvre, Traceability is not meant to reduce uncertainty. Accred. Qual. Assur. 8, 497 (2003)
J. de Boer, On the history of quantity calculus and the international system. Metrologia 31, 405–429 (1994/5)
K.G. Denbigh, J.S. Denbigh, Entropy in Relation to Incomplete Knowledge (Cambridge University Press, Cambridge, 1985). ISBN 0 521 25677 1
P.A.M. Dirac, The principles of quantum mechanics, in The International Series of Monographs on Physics, ed. by J. Birman et al., 4th edn., (Clarendon Press, Oxford, 1992)
S. Ellison, T. Fearn, Characterising the performance of qualitative analytical methods: statistics and terminology. TRAC-Trend Anal. Chem. 24, 468–476 (2005)
W.H. Emerson, On quantity calculus and units of measurement. Metrologia 45, 134–138 (2008)
EN 15224:2012, Health care services – Quality management systems – Requirements based on EN ISO 9001:2008
W.P. Fisher, Jr., Physical disability construct convergence across instruments: Towards a universal metric. Journal of Outcome Measurement 1(2), pp 87–113 (1997)
R. Feynman, The Feynman Lectures on Physics, vol. I, (2013), http://www.feynmanlectures.caltech.edu/I_01.html#Ch1-S1
D. Flater, Redressing grievances with the treatment of dimensionless quantities in SI. Measurement 109, 105–110 (2017)
R. Fleischmann, Einheiteninvariante Gröβengleichungen, Dimension. Der Mathematische und Naturwissenschaftliche Unterricht 12, 386–399 (1960)
A. Gillespie, F. Cornish, Intersubjectivity: towards a dialogical analysis. J. Theory Soc. Behav. 40, 19–46 (2010)
G. Gooday, in The Values of Precision, ed. by M. N. Wise, (Princeton University Press, Princeton, 1995). ISBN 0-691-03759-0
W. Hardcastle, Qualitative Analysis: A Guide to Best Practice (Royal Society of Chemistry, Cambridge, 1998)
S.M. Humphry, The role of the unit in physics and psychometrics. Meas. Interdiscip. Res. Perspect. 9(1), 1–24 (2011)
S.M. Humphry, D. Andrich, Understanding the unit implicit in the Rasch model. J. Appl. Meas. 9, 249–264 (2008)
R.J. Irwin, A psychophysical interpretation of Rasch’s psychometric principle of specific objectivity. Proc. Fechner Day 23, 1–6 (2007)
JCGM200:2012 International vocabulary of metrology—basic and general concepts and associated terms (VIM 3rd edition) (JCGM 200:2008 with minor corrections) WG2 Joint Committee on Guides in Metrology (JCGM) (Sevrès: BIPM)
H. Källgren, M. Lauwaars, B. Magnusson, L.R. Pendrill, P. Taylor, Role of measurement uncertainty in conformity assessment in legal metrology and trade. Accred. Qual. Assur. 8, 541–547 (2003)
M. Kaltoft, M. Cunich, G. Salkeld, J. Dowie, Assessing decision quality in patient-centred care requires a preference-sensitive measure. J. Health Serv. Res. Policy 19, 110–117 (2014). https://doi.org/10.1177/1355819613511076
G.J. Klir, T.A. Folger, Fuzzy sets, uncertainty and information (Prentice Hall, New Jersey, 1988). ISBN 0-13-345984-5
J. Kogan, An Alternative Path to a New SI, Part 1: On Quantities with Dimension One, (2014), https://web.archive.org/web/20160912224601/http://metrologybytes.net/PapersUnpub/Kogan_2014.pdf
L.D. Landau, E.M. Lifshitz, Mechanics, Course of Theoretical Physics (Butterworth-Heinenann, 1976), 3rd ed., Vol. 1. ISBN 0-7506-2896-0.
B. Langefors, Essays on Infology, in Gothenburg Studies of Information Systems, ed. by B. Dahlbom. Report 5 (University of Göteborg, 1993)
J.M. Linacre, B. Wright, The ‘length’ of a Logit. Rasch Meas. Trans. 3, 54–55 (1989)
L. Marco-Ruiz, A. Budrionis, K.Y. Yigzaw, J.G. Bellika, Interoperability Mechanisms of Clinical Decision Support Systems: A Systematic Review, in Proceedings of the 14th Scandinavian Conference on Health Informatics, Gothenburg, Sweden, April 6–7, 2016, (2016). http://www.ep.liu.se/ecp/122/ecp16122.pdf
L. Mari, A. Maul, D. Torres Irribarra, M. Wilson, A metastructural understanding of measurement. J. Phys. Conf. Ser 772, 012009 (2016). IMEKO2016 TC1-TC7-TC13
L. Mari, C.D. Ehrlich, L.R. Pendrill, Measurement units as quantities of objects or values of quantities: a discussion. Metrologia 55, 716 (2018). https://doi.org/10.1088/1681-7575/aad8d8
A. Maul, D. Torres Irribarra, M. Wilson, On the philosophical foundations of psychological measurement. Measurement 79, 311–320 (2016)
A. Maul. Rethinking traditional methods of survey validation, Measurement. Interdisciplinary Research and Perspectives 15(2), 51–56 (2017)
P McCullagh, Regression models for ordinal data. J. Roy. Stat. Soc., 42: p. 109–42 (1980)
A. Mencattini, L. Mari, A conceptual framework for concept definition in measurement: the case of ‘sensitivity. Measurement 72, 77–87 (2015)
G.A. Miller, The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol. Rev. 63, 81–97 (1956)
F. Mosteller, J.W. Tukey, Data Analysis and Regression: A Second Course in Statistics (Addison-Wesley, Reading, 1977)
MRA, International equivalence of measurements: the CIPM MRA, (1999), https://www.bipm.org/en/cipm-mra/
R.R. Nelson, Physics envy: get over it. Iss. Sci. Technol. XXXI, 71–78 (2015). http://issues.org/31-3/physics-envy-get-over-it/
J. Pearce, Psychometrics in action, science as practice. Adv. Health Sci. Educ. 23, 653–663 (2018). https://doi.org/10.1007/s10459-017-9789-7
L.R. Pendrill, Assuring measurement quality in person-centred healthcare. Meas. Sci. Technol 29(3), 034003 (2018). https://doi.org/10.1088/1361-6501/aa9cd2. special issue Metrologie 2017.
L.R. Pendrill, Some comments on fundamental constants and units of measurement related to precise measurements with trapped charged particles. Phys. Scripta T59, 46–52 (1994). (1995) and World Scientific Publishing, ed. I Bergström, C Carlberg & R Schuch, ISBN 981-02-2481-8 (1996)
L.R. Pendrill, Macroscopic and microscopic polarisabilities of helium gas. J. Phys. B At. Mol. Opt. Phys. 29, 3581–3586 (1996)
L.R. Pendrill, Meeting future needs for metrological traceability – a physicist’s view. Accred. Qual. Assur. 10, 133–139 (2005). http://www.springerlink.com/content/0dn6x90cmr8hq3v4/?p=2338bc01ade44a208a2d8fb148ecd37a&pi
L.R. Pendrill, Metrology: time for a new look at the physics of traceable measurement? Europhysics News 37, 22–25 (2006a). https://doi.org/10.1051/epn:2006104
L.R. Pendrill, Optimised measurement uncertainty and decision-making when sampling by variables or by attribute. Measurement 39(9), 829–840 (2006b). https://doi.org/10.1016/j.measurement.2006.04.014
L.R. Pendrill, Uncertainty & risks in decision-making in qualitative measurement, in AMCTM 2011 International Conference on Advanced Mathematical and Computational Tools in Metrology and Testing, Göteborg June 20–22 2011, (2011), http://www.sp.se/AMCTM2011
L.R. Pendrill, Using measurement uncertainty in decision-making & conformity assessment. Metrologia 51, S206 (2014)
K. Pesudovs, Item banking: a generational change in patient-reported outcome measurement. Optom. Vis. Sci. 87(4), 285–293 (2010). https://doi.org/10.1097/OPX.0b013e3181d408d7
B.W. Petley, The fundamental physical constants and the frontier of measurement (Adam Hilger Ltd, Bristol, 1985). ISBN 0-85274-427-7
B.W. Petley, Thirty years (or so) of the SI. Meas. Sci. Technol. 1, 1261 (1990). https://doi.org/10.1088/0957-0233/1/11/023
T. J. Quinn, Metrology, its role in today’s world BIPM Rapport BIPM-94/5 (1994)
A.P. Raposo, The Algebraic Structure of Quantity Calculus, (2016), arXiv:1611.01502v1
G. Rasch, On general laws and the meaning of measurement in psychology, in Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, (University of California Press, Berkeley, 1961), pp. 321–334
F.S. Roberts, Measurement theory with applications to decision-making, utility, and the social sciences, in Encyclopedia of Mathematics and Its Applications, vol. 7, (Cambridge University Press, Cambridge, 1985). ISBN 978-0-521-30227-2
G.B. Rossi, Measurement and probability – a probabilistic theory of measurement with applications, in Springer Series in Measurement Science and Technology, (2014), https://doi.org/10.1007/978-94-017-8825-0
T.D. Schneider, G.D. Stormo, L. Gold, A. Ehrenfeuch, The information content of binding sites on nucleotide sequences. J. Mol. Biol. 188, 415–431 (1986). www.lecb.ncifcrf.gov/~toms/paper/schneider1986
M.M. Schnore, J.T. Partington, Immediate memory for visual patterns: symmetry and amount of information. Psychon. Sci. 8, 421–422 (1967)
C.E. Shannon, W.W.Weaver The mathematical theory of communications. University of Illinois Press, Urbana, 117 p. (1963)
K.D. Sommer, B.R.L. Siebert, Systematic approach to the modelling of measurements for uncertainty evaluation. Metrologia 43, S200–S210 (2006). https://doi.org/10.1088/0026.1394/43/4/S06
A.J. Stenner, M. Smith III, D.S. Burdick, Toward a theory of construct definition. J. Educ. Meas. 20(4), 305–316 (1983)
A.J. Stenner, W.P. Fisher Jr., M.H. Stone, D.S. Burdick, Causal Rasch models. Front. Psychol. 4(536), 1–14 (2013)
S.S. Stevens, On the theory of scales of measurement. Science 103(2684), 677–680 (1946). New Series
L. Tsu, Tao Te Ching, Chapter 71 (Vintage Books (Random House), New York, 1972)
J.A. Tukey, Chapter 8, Data analysis and behavioural science, in The Collected Works of John A Tukey, Volume III, Philosophy and Principles of Data Analysis: 1949 – 1964, ed. by L. V. Jones, (University North Carolina, Chapel Hill, 1986)
P.F. Velleman, L. Wilkinson, Nominal, ordinal, interval, and ratio typologies are misleading. Am. Stat. 47, 65–72 (1993). https://www.cs.uic.edu/~wilkinson/Publications/stevens.pdf
T. Vosk, Measurement uncertainty: requirement for admission of forensic science evidence, in Wiley Encyclopedia of Forensic Science, ed. by A. Jamieson, A. A. Moenssens, (Wiley, Chichester, 2015)
J. Wallot, Dimensionen, Einheiten, Massysteme, in Handbuch der Physik II, Kap. I, (Springer, Berlin, 1926)
W. Weaver, C. Shannon, The Mathematical Theory of Communication (University of Illinois Press, Champaign, 1963). ISBN 0252725484
E.D. Weinberger, A theory of pragmatic information and its application to the quasi-species model of biological evolution. Biosystems 66, 105–119 (2003). http://arxiv.org/abs/nlin.AO/0105030
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Pendrill, L. (2019). Ensuring Traceability. In: Quality Assured Measurement. Springer Series in Measurement Science and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-28695-8_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-28695-8_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-28694-1
Online ISBN: 978-3-030-28695-8
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)