Significant implications arise when we redefine the fundamental nature of data for use across society:
The metrology and framing of the data to be gathered [1] will become vitally important. Making it important that we use “measurement uncertainties” to design ‘data harvesting’ plans and user instructions.[2]
This suggests that there is a need to:
(i) Develop an entirely new educational & scholarly UD discipline;
(ii) Develop UD Big Data computing certification programs;
(iii) Develop UD as a basic skill set in pre-college schooling.[3]
Uncertainties Design or UD will touch the entirety of Data Pre-Harvest Planning.
It will be used to design Uncertainty Measures for a wide range of subjects including: Accounting, Finance, Tax Law, Investing, Trading, Governance, Long-Term Climate Strategies, Ecosystems Stewardship, Weather, Energy, Food, Water, Sustainable Cities, and Economics Forecasting.
Notes
[1] In February 2019, researchers reported the results of a study which concludes that “students would probably exercise better judgement, say the researchers, if they knew more about measurement uncertainties and had a framework for determining when a difference is significant—things that are often left out of the curriculum.” cf. http://physicsbuzz.physicscentral.com/2019/02/more-data-can-lead-to-worse-decisions.html?m=1 and https://journals.aps.org/prper/abstract/10.1103/PhysRevPhysEducRes.15.010103;
[2] 06 February 2019 at 17:21 pm by email: Proposing “Uncertainties Design” to the researchers of Note [1] at Humboldt-Universität zu Berlin and Hofstra University: and to George Verghese (PhD, Curtin University).
[3] ‘ “Given what’s at stake, the researchers recommend that teachers make time to include these concepts in science classrooms and beyond.” ‘ “Since data, and judging the quality of this data, is becoming so prominent in our everyday lives, teachers in all subjects should try to incorporate this into their classes,” they write.” cf. Ibid., http://physicsbuzz.
Image: No-charge download from Pixabay
