Statistical flow data such as commuting, migration, trade and money flows has gained manyinterests from policy makers, city planners, researchers and ordinary citizens as well. Therehave appeared numerous statistical data visualisations; however, there is a shortage of applicationsfor visualising flow data. Moreover, among these rare applications, some are standaloneand only for expert usages, some do not support interactive functionalities, and somecan only provide an overview of data. Therefore, in this thesis, I develop a web-enabled,highly interactive and analysis support statistical flow data visualisation application that addressesall those challenges.My application is implemented based on GAV Flash, a powerful interactive visualisationcomponent framework, thus it is inherently web-enabled with basic interactive features. Theapplication uses visual analytics approach that combines both data analysis and interactivevisualisation to solve cluttering issue, the problem of overlapping flows on the display. A varietyof analysis means are provided to analyse flow data efficiently including analysing bothflow directions simultaneously, visualising time-series flow data, finding most attracting regionsand figuring out the reason behind derived patterns. The application also supportssharing knowledge between colleagues by providing story-telling mechanism which allowsusers to create and share their findings as a visualisation story. Last but not least, the applicationenables users to embed the visualisation based on the story into an ordinary web-pageso that public stand a golden chance to derive an insight into officially statistical flow data.