期刊
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
卷 28, 期 4, 页码 1967-1981出版社
IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2020.3023537
关键词
Data visualization; Correlation; Task analysis; Data analysis; Taxonomy; Natural language processing; Information visualization; natural language generation; natural language processing; human-computer interaction
资金
- UK Engineering and Physical Sciences Research Council (EPSRC) [EP/P025501/1]
This article describes two studies aiming to identify characteristics of data and charts that are relevant in supporting data analysis through language and visualization interaction. The studies reveal that participants use a variety of vocabulary to describe scatterplots, but specific concepts are preferred for higher levels of correlation.
Natural language and visualization are being increasingly deployed together for supporting data analysis in different ways, from multimodal interaction to enriched data summaries and insights. Yet, researchers still lack systematic knowledge on how viewers verbalize their interpretations of visualizations, and how they interpret verbalizations of visualizations in such contexts. We describe two studies aimed at identifying characteristics of data and charts that are relevant in such tasks. The first study asks participants to verbalize what they see in scatterplots that depict various levels of correlations. The second study then asks participants to choose visualizations that match a given verbal description of correlation. We extract key concepts from responses, organize them in a taxonomy and analyze the categorized responses. We observe that participants use a wide range of vocabulary across all scatterplots, but particular concepts are preferred for higher levels of correlation. A comparison between the studies reveals the ambiguity of some of the concepts. We discuss how the results could inform the design of multimodal representations aligned with the data and analytical tasks, and present a research roadmap to deepen the understanding about visualizations and natural language.
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