Visualising Multi-objective Data: From League Tables to Optimisers, and Back

Abstract: League tables are ubiquitous in modern life, and describe the performance of individuals, such as schools, universities, hospitals and countries. Each individual is described according to a set of key performance indicators (KPIs), which are often aggregated to provide a single score by which the set of individuals can be ranked. Visualising individuals according to the full set of KPIs is a better alternative, preventing the unavoidable loss of information that results from aggregation. This talk presents methodologies for visualising according to multiple conflicting measures of performance, taking into account the preference information that characterises this type of data, with examples including university league tables, water quality monitoring, and visualising solutions to multi- and many-objective optimisation problems.