Abstract

Nesting is the embedding of charts into the marks of another chart. Related to principles such as Tufte’s rule of utilizing micro/macro readings, nested visualizations have been employed to increase information density, providing compact representations of multi-dimensional and multi-typed data entities. Visual authoring tools are becoming increasingly prevalent, as they make visualization technology accessible to non-expert users such as data journalists, but existing frameworks provide no or only very limited functionality related to the creation of nested visualizations. In this paper, we present an interactive visual approach for the flexible generation of nested multilayer visualizations. Based on a hierarchical representation of nesting relationships coupled with a highly customizable mechanism for specifying data mappings, we contribute a flexible framework that enables defining and editing data-driven multi-level visualizations. As a demonstration of the viability of our framework, we contribute a visual builder for exploring, customizing and switching between different designs, along with example visualizations to demonstrate the range of expression. The resulting system allows for the generation of complex nested charts with a high degree of flexibility and fluidity using a drag and drop interface.

Highlights

  • Nesting or embedding, i.e., the integration of additional visualizations into the marks of a chart, enables the presentation of information-dense graphical data depictions

  • The full functionality of our framework is exposed in the form of a visual builder, and we demonstrate that our approach allows for the easy generation of a variety of complex nested visualizations

  • We introduced the Visception Tree (VC-tree) as a unified framework for the creation and manipulation of nested visualizations and demonstrated how it can be used to flexibly specify a wide variety of data groupings and visual mappings

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Summary

Introduction

I.e., the integration of additional visualizations into the marks of a chart, enables the presentation of information-dense graphical data depictions. A new generation of visual authoring systems such as Data Illustrator [1] and Charticulator [2] have been developed to enable the creation of custom charts via intuitive visual interfaces accessible to non-experts. They aim to support the flexibility and customization options of design tools such as Adobe Illustrator, while still providing a data-driven visualization environment. While these systems feature advanced mechanisms for designing bespoke charts, they provide no or only very limited support for nesting

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