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A framework for hierarchical time-oriented data visualisation

Henkin, R. (2018). A framework for hierarchical time-oriented data visualisation. (Unpublished Doctoral thesis, City, University of London)

Abstract

The paradigm of exploratory data analysis advocates the use of multiple perspectives to formulate hypotheses on the data. This thesis presents a framework to support it through the use of interactive hierarchical visualisations for the exploration of temporal data. The research that leads to the framework involves investigating what are the conventional interactive techniques for temporal data, how they can be combined with hierarchical methods and which are the conceptual transformations that enable navigating between multiple perspectives. The aim of the research is to facilitate the design of interactive visualisations based on the use of granularities or units of time, which hide or reveal processes at various scales and is a key aspect of temporal data. Characteristics of granularities are suitable for hierarchical visualisations as evidenced in the literature. However, current conceptual models and frameworks lack means to incorporate characteristics of granularities as an integral part of visualisation design. The research addresses this by combining features of hierarchical and time-oriented visualisations and enabling systematic re-configuration of visualisations. Current techniques for visualising temporal data are analysed and specified at previously unsupported levels by breaking down visual encodings into decomposed layers, which can be arranged and recombined through hierarchical composition methods. Afterwards, the transformations of the properties of temporal data are defined by drawing from the interactions found in the literature and formalising them as a set of conceptual operators. The complete framework is introduced by combining the different components that form it and enable specifying visual encodings, hierarchical compositions and the temporal transformations. A case study then demonstrates how the framework can be used and its benefits for evaluating analysis strategies in visual exploration.

Publication Type: Thesis (Doctoral)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Doctoral Theses
Doctoral Theses > School of Mathematics, Computer Science and Engineering Doctoral Theses
School of Mathematics, Computer Science & Engineering > Computer Science
URI: http://openaccess.city.ac.uk/id/eprint/20611
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