The Why and The How: A Survey on Natural Language Interaction in Visualization

Henrik Voigt, Ozge Alacam, Monique Meuschke, Kai Lawonn, Sina Zarrieß


Abstract
Natural language as a modality of interaction is becoming increasingly popular in the field of visualization. In addition to the popular query interfaces, other language-based interactions such as annotations, recommendations, explanations, or documentation experience growing interest. In this survey, we provide an overview of natural language-based interaction in the research area of visualization. We discuss a renowned taxonomy of visualization tasks and classify 119 related works to illustrate the state-of-the-art of how current natural language interfaces support their performance. We examine applied NLP methods and discuss human-machine dialogue structures with a focus on initiative, duration, and communicative functions in recent visualization-oriented dialogue interfaces. Based on this overview, we point out interesting areas for the future application of NLP methods in the field of visualization.
Anthology ID:
2022.naacl-main.27
Volume:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
July
Year:
2022
Address:
Seattle, United States
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
348–374
Language:
URL:
https://aclanthology.org/2022.naacl-main.27
DOI:
10.18653/v1/2022.naacl-main.27
Bibkey:
Cite (ACL):
Henrik Voigt, Ozge Alacam, Monique Meuschke, Kai Lawonn, and Sina Zarrieß. 2022. The Why and The How: A Survey on Natural Language Interaction in Visualization. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 348–374, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
The Why and The How: A Survey on Natural Language Interaction in Visualization (Voigt et al., NAACL 2022)
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PDF:
https://aclanthology.org/2022.naacl-main.27.pdf