Authors: Albert Amor-Amorós, Paolo Federico, Silvia Miksch
Abstract: Large multivariate time-oriented networks have been gaining an increasing relevance in different domains. In order to support Visual Analytics processes on this kind of data, appropriate storage and retrieval methods are needed that take into account the scale, dimensionality, and in particular the complex nature of time. We introduce TimeGraph, a data management framework consisting of a data model and two levels of abstraction. TimeGraph captures both the topology of networks and the inherent structure of time into a property graph data structure, and transparently handles them by graph-based operations. TimeGraph aims to be an expressive, easy- to-use and extensible framework, enabling data reduction by selection and aggregation over both the temporal and the topological properties of data, to foster interactive visualization and analysis.