CRS ICT4D Conference

Indicators are recognized as useful quantitative tools that assist in prioritizing operations of international organizations and influencing national policies. The quantitative representation of different phenomena in diverse fields allows institutions to monitor national progress over time (time-series) and benchmark nations through cross-country comparisons. Often, however, some indices do not provide adequate visualization nor interpretation tools. ICT illiterate policymakers and other stakeholders at different levels of the government would welcome such supporting resources, particularly if they can provide real-time interpretation of new or updated data, thus fulfilling an important principle of information, timeliness. Some stakeholders would also welcome tools that enable them reproducing indices or even creating their own indices. This would also fulfill an important principle of data and information, transparency. In the presentation, we elaborate further on the challenges in data acquisition for building up indicators. In this context, we introduce a package that includes different user-centered tools that was developed while implementing the Notre Dame Global Adaptation Index (ND-GAIN). ND-GAIN is a leading index that summarizes a country's vulnerability to climate change and other global challenges in combination with its readiness to improve resilience. The index is characterized for its transparency, the open data nature of their constituent indicators, and the actionability of them. The presentation showcases the following tools through their application to the African nation of Burundi, one of the nations that is the focus of several CRS programs: i) tools for acquiring real-time data from the World Bank and other institutions that provide open data through an API (application programmable interface), ii) tools for building up an index based on frameworks created by the user, iii) tools for generating meaning based on statistical analyses of such data, iv) tools for drawing generalized conclusions from such data, and v) tools for visualizing such data.