Composite Indicators (CIs), are a common measurement and benchmarking tool that are used to reflect and measure multidimensional concepts such as digital divides, individual's well-being and more. Measurement iterations produce a series of time-oriented data, which stakeholders as well as the general public might be interested to interpret. Visualization of a CI is highly recommended in order to ease interpretation, and many CI websites use radial solutions to visualize CIs. Yet it is unclear how to visualize the temporal dynamics in radial diagrams. Static solutions, mapping time to small multiples might be challenging due to screen space issues. Dynamic solutions are appealing, yet, there is no clear empirical evidence on benefits of dynamic time coding in radial diagrams. In this paper, we compare static vs. dynamic time mapping using two radial CI visualization methods. The popular Radar chart technique is compared to the innovative Flower chart as used in the well-known OECD Better Life index. We compare users' performance and preferences empirically under formal task taxonomy, adjusted to CI tasks. Results indicate that in general, static time encoding was more effective than dynamic encoding. Still, an in depth analysis showed that the dynamic approach is a feasible and sometimes even better solution for important CIs tasks, leveraged by the fact that users seem to like and enjoy it.

A composite indicator (CI) is a measuring and benchmark tool used to capture multi-dimensional concepts, such as Information and Communication Technology (ICT) usage. Individual indicators are selected and combined to reflect a phenomena being measured. Visualization of a composite indicator is recommended as a tool to enable interested stakeholders, as well as the public audience, to better understand the indicator components and evolution over time. However, existing CI visualizations introduce a variety of solutions and there is a lack in CI's visualization guidelines. Radial visualizations are popular among these solutions because of CI's inherent multi-dimensionality. Although in dispute, Radar-charts are often used for CI presentation. However, no empirical evidence on Radar's effectiveness and efficiency for common CI tasks is available. In this paper, we aim to fill this gap by reporting on a controlled experiment that compares the Radar chart technique with two other radial visualization methods: Flower-charts as used in the well-known OECD Betterlife index, and Circle-charts which could be adopted for this purpose. Examples of these charts in the current context are shown in Figure 1. We evaluated these charts, showing the same data with each of the mentioned techniques applying small multiple views for different dimensions of the data. We compared users' performance and preference empirically under a formal task-taxonomy. Results indicate that the Radar chart was the least effective and least liked, while performance of the two other options were mixed and dependent on the task. Results also showed strong preference of participants toward the Flower chart. Summarizing our results, we provide specific design guidelines for composite indicator visualization. Fig. 1: Three radial solutions for composite indicator visualizations compared empirically for users' performance and preferences.