Science Explorer Interactive view Map

Scientific Measurement and Uncertainty Evaluation

Scientific Measurement and Uncertainty Evaluation is a research topic within Statistics, Probability and Uncertainty. Science Explorer counts 25k research works in it since 1950. 14.4% of them reached the world's top 10% most cited for their field and year.

This cluster of papers covers advancements in measurement techniques, uncertainty evaluation, and the redefinition of SI units. It includes topics such as the determination of fundamental constants like the Avogadro constant and Planck constant, the use of Monte Carlo methods for uncertainty estimation, and the development of new approaches for expressing measurement uncertainty. Additionally, it explores the quality assurance standards and the evaluation of reference materials in metrology.

  • Measurement Uncertainty
  • Redefinition of SI Units
  • Avogadro Constant
  • Planck Constant
  • Watt Balance
  • Monte Carlo Method
  • Reference Materials
  • Bayesian Statistics
  • Quality Assurance
  • Atomic Weight Determination
Research works
25k
fractional, since 1950
In the world top 10%
3.6k
per year above
Top-10% rate
14.4%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-4%
the tick is no change

Which countries lead Scientific Measurement and Uncertainty Evaluation research?

By volume, China and the United States publish the most (310 and 308 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 310 works
  2. 2 United States 308 works
  3. 3 Germany 182 works
  4. 4 Russia 149 works
  5. 5 India 103 works
  6. 6 United Kingdom 89 works
  7. 7 Italy 89 works
  8. 8 France 74 works
  9. 9 Japan 64 works
  10. 10 Brazil 55 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 21.8%United States: 21.6%Germany: 12.8%Russia: 10.5%6 others listed: 33.3%22%largest
China310 · 21.8%United States308 · 21.6%Germany182 · 12.8%Russia149 · 10.5%6 others listed475 · 33.3%

Shares of the rows listed above, not of the whole node.

Which institutions lead Scientific Measurement and Uncertainty Evaluation research?

By volume in 2022–2025, Physikalisch-Technische Bundesanstalt publishes the most Scientific Measurement and Uncertainty Evaluation research, followed by National Institute of Standards and Technology and D.I. Mendeleyev Institute for Metrology.

Who are the leading researchers in Scientific Measurement and Uncertainty Evaluation?

The most-cited researchers publishing on Scientific Measurement and Uncertainty Evaluation include R. J. Barlow.

  1. 1 R. J. Barlow United Kingdom 5.2k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Scientific Measurement and Uncertainty Evaluation research done?

The largest centres of Scientific Measurement and Uncertainty Evaluation research in 2022–2025 are Beijing (China), Moscow (Russia), Saint Petersburg (Russia) and Braunschweig (Germany). Among places with at least 20 works in it, it is an unusually large share of all research in Gaithersburg, Braunschweig and Turin.

Largest cities, 2022–2025

  1. 1 Beijing China 77 works
  2. 2 Moscow Russia 60 works
  3. 3 Saint Petersburg Russia 45 works
  4. 4 Braunschweig Germany 43 works
  5. 5 London United Kingdom 36 works
  6. 6 Gaithersburg United States 31 works
  7. 7 Shanghai China 27 works
  8. 8 Turin Italy 24 works
  9. 9 Paris France 23 works
  10. 10 Xi'an China 23 works

Where it is the local speciality

  1. GaithersburgUS · 30.8 works71×
  2. BraunschweigDE · 43.4 works55×
  3. TurinIT · 23.6 works9.2×
  4. TsukubaJP · 21.4 works9.0×
  5. Saint PetersburgRU · 44.5 works7.6×
← less than its size predictsmore →

Location quotient: how much more of its research is in Scientific Measurement and Uncertainty Evaluation than the world average.

See Scientific Measurement and Uncertainty Evaluation on the map

Where is the best place to study Scientific Measurement and Uncertainty Evaluation?

Among universities, judged by research, Quaid-i-Azam University, King Mongkut's University of Technology North Bangkok and Xi'an Jiaotong University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%10%20%mean 11.85%fractional works in this node (log) →share in the world top 10% →Quaid-i-Azam University: 10, 6.0%King Mongkut's University of Technology North Bangkok: 16, 11.3%Xi'an Jiaotong University: 10, 21.9%Politecnico di Milano: 9, 16.8%Tsinghua University: 8, 15.1%Sapienza University of Rome: 10, 0.0%Xi'an Jiaotong Unive…Politecnico di MilanoKing Mongkut's Unive…Quaid-i-Azam Univers…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Quaid-i-Azam UniversityPakistan 60.66.0%30.7×10 +464.4%
2 King Mongkut's University of Technology North BangkokThailand 60.211.3%59.3×16 +61.9%
3 Xi'an Jiaotong UniversityChina 48.321.9%3.0×10 +108.9%
4 Politecnico di MilanoItaly 42.016.8%5.7×9 -32.3%
5 Tsinghua UniversityChina 26.915.1%2.0×8 -8.2%
6 Sapienza University of RomeItaly 13.80.0%4.3×10 -49.8%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Scientific Measurement and Uncertainty Evaluation research growing?

Output in 2018–2022 was 4% lower than in 2013–2017, peaking in 2018. The fastest-growing topics are Scientific Measurement and Uncertainty Evaluation.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.