The analysis of large sets of spatio-temporal data is a fundamental challenge in epidemiological research. As the quantity and the complexity of such kind of data increases, automatic analysis approaches, such as statistics, data mining, machine learning, etc., can be used to extract useful information. While these approaches have proven effective, they require a priori knowledge of the information being sought, and some interesting insights into the data may be missed. To bridge this gap, information visualizatio…

In the context of graph layout, many algorithms have been designed to remove node overlapping, and many quality criteria and associated metrics have been proposed to evaluate those algorithms. Unfortunately, a complete comparison of the algorithms based on some metrics that evaluate their quality has never been provided and it is thus difficult for a visualisation designer to select the algorithm that best suits their needs. In this paper, we review 22 metrics available in the literature, classify them according t…

Many algorithms have been designed to remove node overlapping, and many quality criteria and associated metrics have been proposed to evaluate those algorithms. Unfortunately, a complete comparison of the algorithms based on some metrics that evaluate the quality has never been provided and it is thus difficult for a visualization designer to select the algorithm that best suits his needs. In this paper, we review 21 metrics available in the literature, classify them according to the quality criteria they try to c…