In recent years, a wide variety of new data sources and innovative data collection tools have been emerging especially in the spatial or geo-referenced data domain. The statistical community has the obligation of exploring the use of such data and tools, including Big Data, open data and remote sensing technologies, to meet the expectation of the society for enhanced products and improved and more efficient ways of working.

Use of advanced data tools, global databases, Big Data and open data could also support the subscription and monitoring of the Sustainable Development Goals (SDGs) by improving international consistency, timeliness, frequency, detail and operational relevance of indicators without compromising their impartiality and methodological soundness. The reports of the UN Committee of Experts on Big Data and Data Science for Official Statistics (UN-CEBD) to the Statistical Commission (E/CN.3/2015/4, E/CN.3/2016/6, E/CN.3/2017/7, E/CN.3/2018/8 and E/CN.3/2019/27) provide additional background to the work of the task teams.

The Rural Access Index (RAI) is one of the most important global development indicators in the transport sector and was adopted as the SDG indicator 9.1.1 to measure the progress of Target: 9.1: Develop quality, reliable, sustainable and resilient infrastructure, including regional and trans-border infrastructure, to support economic development and human well-being, with a focus on affordable and equitable access for all. The index was developed by the World Bank in 2006 and aims at measuring the share of rural population who has access to all-season roads, conventionally, within 2 km, or equivalently, 25-minute walking distance. In the original work, with limited household surveys used at that time, it was estimated that about 900 million rural people were estimated to have no access to the road network – as often referred to as “1 billion people without access.”

In the SDG context, the Bank developed a new methodology for RAI in collaboration with the donor community, aimed at ensuring (i) consistency, (ii) sustainability, (iii) ownership, and (iv) operational relevance of the indicator. The new methodology relies on spatial data and techniques that are newly available:

• Formal definition. The indicator is defined as the proportion of the rural population who live within 2 km of an all-season road.
• Main data sources. The new methodology relies on (i) global population distribution datasets, (ii) road network data, and (iii) road condition data.
• Computation. Overlaying these datasets, the number of population who live in 2km of a good road is calculated.

The developed methodology has been applied to 8 pilot countries in the 2016 report (Bangladesh, Nepal, Ethiopia, Kenya, Mozambique, Tanzania, Uganda and Zambia), and 15 additional countries in the 2017/18 update report (Armenia, Burundi, Lesotho, Liberia, Madagascar, Malawi, Mali, Nigeria, Peru, Rwanda, Sierra Leone, Somalia, Iraq, Jordan and Lebanon). Bilateral follow-up consultations are continued, which generate new RAI estimates for other countries. Some additional information related to the proposed work can be found in the World Bank Development Data Hub: Rural Access Index.