Low-cost GIS for water resources

Low-cost GIS for water resource

Quantifying and Mapping Global Data Poverty.

Digital information technologies, such as the Internet, mobile phones and social media, provide vast amounts of data for decision-making and resource management. However, access to these technologies, as well as their associated software and training materials, is not evenly distributed: since the 1990s there has been concern about a "Digital Divide" between the data-rich and the data-poor. We present an innovative metric for evaluating international variations in access to digital data: the Data Poverty Index (DPI). The DPI is based on Internet speeds, numbers of computer owners and Internet users, mobile phone ownership and network coverage, as well as provision of higher education. The datasets used to produce the DPI are provided annually for almost all the countries of the world and can be freely downloaded. The index that we present in this 'proof of concept' study is the first to quantify and visualise the problem of global data poverty, using the most recent datasets, for 2013. The effects of severe data poverty, particularly limited access to geoinformatic data, free software and online training materials, are discussed in the context of sustainable development and disaster risk reduction. 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 Sendai Framework for Disaster Risk Reduction

Overview of the average DPI factor scores compared to the World Bank income classification.

<p>Overview of the average DPI factor scores compared to the World Bank income classification.</p

Map showing global Data Poverty for 2013, by nation states.

<p>The locations of the 50 most populous cities are also shown. The base map (world borders) was obtained from <a href="http://diva-gis.org/data" target="_blank">http://diva-gis.org/data</a>.</p

Weblinks for data sources used for the DPI factors.

<p>* Since mid-2015 the netindex.com website is no longer accessible; however an alternative source of Internet Speed data is: <a href="http://www.ookla.com" target="_blank">http://www.ookla.com</a>.</p><p>Weblinks for data sources used for the DPI factors.</p

Example scores of the Data Poverty Index (DPI) and relationships to the World Bank income classification.

<p>Scores: < 1.21, high data poverty; 1.21–2.42, above average data poverty; 2.42–3.62, below average data poverty; > 3.62, low data poverty. Remark: Only countries with a complete dataset have been considered.</p><p>* China Mainland, excluding Macao and Hong Kong.</p><p>Example scores of the Data Poverty Index (DPI) and relationships to the World Bank income classification.</p

Data sets input to calculate the Data Poverty Index.

<p>Data sets input to calculate the Data Poverty Index.</p