239
© Springer Nature Switzerland AG 2021
L. Mari et al., Measurement across the Sciences, Springer Series in
Measurement Science and Technology,
https://doi.org/10.1007/978-3-030-65558-7_8
Chapter 8
Conclusion
8.1 Introduction
Measurement is a designed, intentional (not spontaneous, not natural) process (it
needs to comply with a procedure, etc.), and as such it is performed for improving
the previously available information about a property of an object: indeed, while
bad and useless measurements are certainly possible, as discussed in Sect. 7.4.4, the
results of a measurement are expected, in principle, to be able to improve the available information. This final chapter is devoted to better exploring the claim that
measurement is designed for producing useful information on the measurand: this
will allow us to identify the sufficient condition to characterize measurement that
we have been seeking from the beginning of this book.
The model of direct measurement presented in Chap. 7 is the basis of the analysis
that follows, in which measurement is interpreted as a tool for communication: first
measurement produces syntactic information (corresponding to local values, i.e.,
values of instrument indication), which is then transformed into semantic information (corresponding to measurement results), which—if the measurement was
appropriately designed and performed—is finally transformed into pragmatic information, and therefore information useful for the purposes that led to the design and
performance of the measurement itself. This interpretation embeds measurement in
semiotics, to which we first provide a short introduction.
© Springer Nature Switzerland AG 2021
L. Mari et al., Measurement across the Sciences, Springer Series in
Measurement Science and Technology,
https://doi.org/10.1007/978-3-030-65558-7_8
Chapter 8
Conclusion
8.1 Introduction
Measurement is a designed, intentional (not spontaneous, not natural) process (it
needs to comply with a procedure, etc.), and as such it is performed for improving
the previously available information about a property of an object: indeed, while
bad and useless measurements are certainly possible, as discussed in Sect. 7.4.4, the
results of a measurement are expected, in principle, to be able to improve the available information. This final chapter is devoted to better exploring the claim that
measurement is designed for producing useful information on the measurand: this
will allow us to identify the sufficient condition to characterize measurement that
we have been seeking from the beginning of this book.
The model of direct measurement presented in Chap. 7 is the basis of the analysis
that follows, in which measurement is interpreted as a tool for communication: first
measurement produces syntactic information (corresponding to local values, i.e.,
values of instrument indication), which is then transformed into semantic information (corresponding to measurement results), which—if the measurement was
appropriately designed and performed—is finally transformed into pragmatic information, and therefore information useful for the purposes that led to the design and
performance of the measurement itself. This interpretation embeds measurement in
semiotics, to which we first provide a short introduction.