Towards Natural Language Interfaces for Data Visualization: A Survey

TL;DR

This survey reviews the development of visualization-oriented natural language interfaces (V-NLI), classifies existing systems across a visualization pipeline, and discusses future research directions in this emerging field.

Contribution

It provides a comprehensive classification framework for V-NLI systems based on an extended visualization pipeline, aiding future research and development.

Findings

Extensive review of V-NLI systems over two decades

Classification framework based on visualization pipeline stages

Identification of promising future research directions

Abstract

Utilizing Visualization-oriented Natural Language Interfaces (V-NLI) as a complementary input modality to direct manipulation for visual analytics can provide an engaging user experience. It enables users to focus on their tasks rather than having to worry about how to operate visualization tools on the interface. In the past two decades, leveraging advanced natural language processing technologies, numerous V-NLI systems have been developed in academic research and commercial software, especially in recent years. In this article, we conduct a comprehensive review of the existing V-NLIs. In order to classify each paper, we develop categorical dimensions based on a classic information visualization pipeline with the extension of a V-NLI layer. The following seven stages are used: query interpretation, data transformation, visual mapping, view transformation, human interaction, dialogue management, and presentation. Finally, we also shed light on several promising directions for future work in the V-NLI community.