Data Poverty

Global Data Poverty

“The information on this website as well as the linked article gives a modern evaluation of the “Digital Divide” concept that was originally developed in the early days of the Internet. The research is of international interest, with implications for sustainable development. Freely available digital information and freeware could greatly enhance sustainable development and disaster risk reduction initiatives, yet most developing countries do not have sufficient access to the internet and mobile phone networks, nor expertise in ICT, to benefit.
The index that we present in this ‘proof of concept’ study is the first to quantify and moreover visualise the problem of global data poverty.
We present an innovative metric for evaluating international variations in access to digital data: the Data Poverty Index (DPI). The DPI highlights countries where support is needed for improving access to the Internet and for the provision of training in geoinfomatics. We conclude that the DPI is of value as a potential metric for monitoring the Sustainable Development Goals of the recent Sendai Framework for Disaster Risk Reduction.
We have opted to submit this paper to PLOS One because it is pioneering in Open Access format and hene a step towards reducing global data poverty.”

Dr. Richard M. Teeuw and Dr. Mathias Leidig

Quantifying and Mapping Global Data Poverty

(click the link above to go to the website to download the article or have a read below)

Supplementary data and graphs to the article:

“Quantifying and Mapping Global Gata Poverty”

  • For a visualisation of the results click here.

Please keep in mind to set the class boundaries as follows to get a representation similar to the one in the article:

  •  >3.6        – high data poverty;
  • 2.4 – 3.6  – above average data poverty;
  • 1.2 – 2.4   – below average data poverty;
  • 0.1 – 1.2    – low data poverty
  • < 0.1         – (includes 0 = no data/ no complete dataset)
  • For a visualisation of the individual factors click here (will be available soon).

Representation as Card:

  • Raw data for the processing can be downloaded here.

Further supplemental data:

The Spider Plot analyse for the average factor values (included in the paper too).


Table 4 colour coded; this was not possible in PLOS-ONE and needed to be changed.

Table 4: Comparison of input variables of global indices dealing with global disaster risk. Colour code: Green: data freely available;  bold red: data not freely available; Brown italic 

Index Used Indicators
Data Poverty Index

o  Factors unweighted

o  Values available online

  • Mobile cellular subscriptions per 100 people;
  • Telephones quality; Percent of population covered by mobile cellular network;
  • Percentage households with a computer;
  • Individuals using the Internet; percentage of population;
  • Tertiary Gross enrollment ratio; % of relevant age group;
  • Country population; Number of universities in a country;
  • Internet upload speed (qualifying date: 10.12.2013);
  • Internet download speed (qualifying date: 10.12.2013)
ICT Development Index 2012 [31]


o  Factors weighted;

o  values only available in report

  • Mobile-cellular telephone subscriptions per 100 inhabitants;
  • Percentage of households with a computer;
  • Fixed (wired)-broadband Internet subscriptions per 100 inhabitants;
  • Secondary gross enrolment ratio;
  • Tertiary gross enrolment ratio;
  • Fixed-telephone lines per 100 inhabitants;
  • Adult literacy rate*1;
  • International Internet bandwidth (bit/s) per Internet user;
  • Active mobile-broadband subscriptions per 100 inhabitants;
World Bank: Index          of Risk Preparation Across Countries (IRPAC) [34]

o  Factor weighting not stated;

o  Values not available

  • Immunization rate for measles;
  • -Percent of the population with access to improved sanitation facilities;
  • Average years of total schooling for the population aged 15 or over;
  • Proportion of households with less than $1,000 in net assets;
  • Percent of the work- force who contribute to a pension scheme;
  • Proportion of respondents stating that “in general, people can be trusted” (social support);
  • Indicator of fiscal space based on gross public debt as a % of revenues (state support);
  • Index of access to finance.
UN World Risk Index 2014 variables [40]


o  Factors weighted (by expert knowledge);

o  Values available in report and online

  • Total population of country ;
  • Share of the population without access to improved sanitation;
  • Share of the population without access to an improved water source;
  • Dependency ratio (share of under 15- and over 65-year-olds in relation to the working population); Number of physicians per 10,000 inhabitants;
  • Number of hospital beds per 10,000 inhabitants;
  • Gross domestic product per capita (purchasing power parity);
  • Adult literacy rate; Combined gross school enrollment;
  • Private health expenditure; Public health expenditure; Gini index;
  • Life expectancy at birth *3; Corruption Perceptions Index*3;
  • Extreme poverty population living with USD 1.25 per day or less *2;
  • Good governance (Failed States Index) *3:
  • Number of people in a country who are exposed to the natural hazards earthquakes (A), cyclones (B) and/or flooding (C) *2;
  • Number of people in this country who are threatened by drought (D) and/or sea level rise (E) (each weighted half owing to the uncertainty of the data base) *2; Gender parity in education *3;
  • Share of female representatives in the National Parliament *3;
  • Water resources*3; Biodiversity and habitat protection*3;
  • Forest management*3; Agricultural management *3;
  • Insurance (life insurance excluded).
*1 dataset freely available but patchy and inconsistent coverage of countries;
*2: data not up-to-date,. last updated in 2007 or 2008;
*3: data is not up-to-date, last updated in 2010.