Literal Encoding: Text is a first-class data encoding

TL;DR

This paper advocates for treating literal text as a fundamental data type in visualizations, highlighting its benefits over traditional visualization methods for digital humanities and semantic analysis.

Contribution

It introduces the concept of literal encoding, emphasizing the importance of text as a first-class data type in visualization design.

Findings

Literal text encoding enhances semantic analysis in visualizations.

Sample visualizations demonstrate benefits over standard graph types.

Text as data improves perceptual and operational understanding.

Abstract

Digital humanities are rooted in text analysis. However, most visualization paradigms use only categoric, ordered or quantitative data. Literal text must be considered a base data type to encode into visualizations. Literal text offers functional, perceptual, cognitive, semantic and operational benefits. These are briefly illustrated with a subset of sample visualizations focused on semantic word sequences, indicating benefits over standard graphs, maps, treemaps, bar charts and narrative layouts.