A Conceptual Framework for Visualizing Composite Indicators

Composite indicators (CIs) are common measurements and benchmarking tools used to measure multidimensional concepts such as well-being, education and more. Indicators and sub-indicators are selected and combined to reflect a measured phenomenon. Measurement iterations produce a series of time-oriented data, which stakeholders, as well as the general public, might be interested in interpreting. Visualization of a CI is highly recommended, in order to facilitate interpretation and enhance understanding of indicator components and their evolution over time. In recent years, a variety of CI visualizations have been published including various visualization techniques. Indeed, visualizing a CI is a complex and challenging issue, involving many design choices. However, there is a lack of guidelines and methodological approaches for CI visualization design. We suggest a framework that provides a systematic way of thinking of CI visualizations. The framework is intended for two uses: as a design tool when constructing a new CI visualization, and as an analytic tool for systematically describing, comparing and evaluating CI visualizations. The suggested framework is the outcome of both a top-down process, based on CI construction and information visualization literature, and a bottom-up process, in which 35 existing visualization applications of popular CIs were analyzed. We use Munzner’s visualization analysis and design framework (Munzner in Visualization analysis and design, CRC Press, Boca Raton, 2014 ) in an adaptive way, considering the specific challenges and characteristics of CI visualizations, in order to develop and discuss a systematic view of the data, tasks and methods for visualizing CIs. We demonstrate the use of the framework with a case study analyzing the popular OECD Better Life Index visualization tool.