A taxonomy of visualization techniques using the data state reference model

TLDR

Previous taxonomies of information visualization techniques have focused on compatible data domains to help implementers identify suitable methods, but they do not explain how to apply or implement those techniques. This paper proposes a new taxonomy of information visualization techniques based on the Data State Model. The taxonomy is constructed by mapping techniques onto the Data State Model’s stages of data transformation. The analysis reveals that many techniques share reusable operating steps and that the Data State Model clarifies both the design space for researchers and the broader applicability for implementers. Data State Model (Chi & Reidl, 1998).

Abstract

In previous work, researchers have attempted to construct taxonomies of information visualization techniques by examining the data domains that are compatible with these techniques. This is useful because implementers can quickly identify various techniques that can be applied to their domain of interest. However, these taxonomies do not help the implementers understand how to apply and implement these techniques. The author extends and proposes a new way to taxonomize information visualization techniques by using the Data State Model (E.H. Chi and J.T. Reidl, 1998). In fact, as the taxonomic analysis in the paper will show, many of the techniques share similar operating steps that can easily be reused. The paper shows that the Data State Model not only helps researchers understand the space of design, but also helps implementers understand how information visualization techniques can be applied more broadly.