Latvia vs United Arab Emirates: Dimension 2.2: Online access - Machine Readability Score

Latvia
0.967
in 2023
United Arab Emirates
0.967
in 2023
Latvia rank
13th
United Arab Emirates rank
13th

Dimension 2.2: Online access - Machine Readability Score over time

  • Latvia
  • United Arab Emirates
00.20.40.60.81201620192023

How they compare

Latvia currently reports 0.967 against 0.967 in United Arab Emirates, a difference of 0.

The two have swapped places 1 time across 8 shared years of data; in 2016 it was Latvia ahead.

Latvia ranks 13th and United Arab Emirates ranks 13th of 177 countries.

Across the 2 decades both report, Latvia averaged higher in 1 and United Arab Emirates in 1.

Head to head by decade

Decade Latvia United Arab Emirates Difference Ahead
2010s 0.902 0.7238 0.1783 Latvia
2020s 0.894 0.9835 0.0895 United Arab Emirates

Averages of every year both report within each decade.

Frequently asked questions

Which has higher dimension 2.2: online access - machine readability score, Latvia or United Arab Emirates?
Latvia, at 0.967 against 0.967 in United Arab Emirates as of 2023.
What is the difference in dimension 2.2: online access - machine readability score between Latvia and United Arab Emirates?
0, with Latvia ahead.
How many years of comparable data are there for Latvia and United Arab Emirates?
8 years are reported by both, from 2016 to 2023.
How do Latvia and United Arab Emirates rank globally for dimension 2.2: online access - machine readability score?
Latvia ranks 13th and United Arab Emirates ranks 13th of 177 countries.
Where does this data come from?
Open Data Watch, published as Dimension 2.2: Online access - Machine Readability Score. Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

About this data

Indicator
Dimension 2.2: Online access - Machine Readability Score
Source
Open Data Watch
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
179 places, 1,551 data points, 2015–2023
Last refreshed

This openness element measures whether data are made available in machine readable formats. Machine readable file formats allow users to easily process data using a computer. Common machine readable formats include XLS, XLSX, CSV, and JSON files.