Module 3 Topic 2 (ICT)
Once we have the raw data component, we might be dealing with thousands or even millions of rows of data. Therefore, it might become difficult to make sense of them and draw conclusions about the issue at hand. That is when data visualization with maps and other graphics play an important role.
Data visualization exposes the underlying patterns and relationships contained within the data. Thus, it makes it easier for the public to understand large databases through visual comparisons, such as budget information. One example can be found in the work that has been done for OpenSpending.org.
According to some experts, web and mobile technologies are helping identify policy priorities and service delivery challenges through data visualization, among other techniques. This practice has led to early successes, such as inequalities in funding allocations that were uncovered through correlating datasets, and accountability feedback loops where CSOs challenged government spending priorities.
Another clear example of the use of visualizations can be found in the Mapping for Results project of the World Bank Group, which visualizes the locations of World Bank-financed projects. It aims at supporting better monitoring of development impact and improving aid effectiveness and coordination, with the ultimate goal of enhancing transparency and social accountability.