Abstract
Over the years, there is a large amount of data being generated in almost all the fields such as engineering, medical, bioscience and social network. To visualise set relationships for a large data is always a challenge, especially with the data evolving over time. There is no tool that supports the set visualisation represented over time. So, we explored this impossibility by developing a novel visual method and a software tool to generate Euler-time diagrams, which will represent set relations with respect to time. The idea was taken from the well-known visualisations: Euler diagrams and time-series. Euler diagrams represent set relations and time-series represent a sequence of events happened over a time. We merged the idea of Euler diagrams and time-series to spark the novelty. Pattern discovery not only plays an important role in graph analysis but also in the set analysis process. In this paper, we took a case study from theWorld Health Organisation (WHO) who is constantly trying to understand relationships between various diseases people are affected over a period of time. This motivated us to develop the set relationship time tool, by considering two levels: aggregation and relationships, using data-driven documents (D3) and Google developing tool kit. This prototype tool can be enhanced by considering gestalt principles, topological properties, perceptual and cognitive theories which will help in analysing and interpreting data efficiently.