It’s been remarkable to me to see the level of excitement generated by the World Bank’s early efforts to “mash-up” the location of development projects within countries with MDG indicators like infant mortality, attended child births, and malnutrition. Being able to visualize correlations between poverty and the location of development projects is sometimes surprising, often encouraging and never uninteresting.
Why are health projects concentrated in parts of country X where life expectancy is high? Where are the water and education projects in country Y in districts with the highest rates of under 5 mortality? The answers are seldom straightforward but good data and simple visualizations can provoke good questions, healthy debates and animate stories of what’s going on. Some will be stories worth celebrating for replication and others will be about lessons learned and things to avoid.
But getting caught-up in the mapping narrative almost misses the point. In a geo-enabled world, many people can create maps and different maps will tell different stories. The key is liberating the underlying data that allows people to create maps in the first place. That’s what has started at the World Bank and where Mapping for Results goes beyond traditional GIS and mapping projects. It’s about geo-enabling the Bank and creating the foundational data that will allow for all kinds of analysis, better planning, better monitoring, and eventually direct engagement with citizens based on actual data.
Disparities within countries (or uneven development) is often more stark than disparities between countries. India and China may be experiencing extraordinary rates of economic growth in the aggregate but what about parts of the country that are getting absolutely or relatively poorer? Is that where aid and public expenditures are focused? Giving researchers, policy makers, media, and civil society groups access to the underlying data and tools to understand data are both critical in promoting increased levels of transparency, accountability, and collaboration in making public services work better.
As much as I love maps and love seeing what our early geo-efforts show (including raising more questions than they answer), what really excites me is the possibility of others taking our geo-referenced data and creating countless maps, apps, analyses, and other mash-ups based on the data we’ve released to the world.