Natural Language Generation for Visualizations: State of the Art, Challenges and Future Directions

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dc.contributor.authorHoque, E.en_US
dc.contributor.authorIslam, M. Saidulen_US
dc.date.accessioned2025-03-07T16:49:36Z
dc.date.available2025-03-07T16:49:36Z
dc.date.issued2024
dc.description.abstractNatural language and visualization are two complementary modalities of human communication that play a crucial role in conveying information effectively. While visualizations help people discover trends, patterns and anomalies in data, natural language descriptions help explain these insights. Thus, combining text with visualizations is a prevalent technique for effectively delivering the core message of the data. Given the rise of natural language generation (NLG), there is a growing interest in automatically creating natural language descriptions for visualizations, which can be used as chart captions, answering questions about charts or telling data‐driven stories. In this survey, we systematically review the state of the art on NLG for visualizations and introduce a taxonomy of the problem. The NLG tasks fall within the domain of natural language interfaces (NLIs) for visualization, an area that has garnered significant attention from both the research community and industry. To narrow down the scope of the survey, we primarily concentrate on the research works that focus on text generation for visualizations. To characterize the NLG problem and the design space of proposed solutions, we pose five Wh‐questions, why and how NLG tasks are performed for visualizations, what the task inputs and outputs are, as well as where and when the generated texts are integrated with visualizations. We categorize the solutions used in the surveyed papers based on these ‘five Wh‐questions’. Finally, we discuss the key challenges and potential avenues for future research in this domain.en_US
dc.description.number1
dc.description.sectionheadersMajor Revision from EuroVis Symposium
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume44
dc.identifier.doi10.1111/cgf.15266
dc.identifier.issn1467-8659
dc.identifier.pages23
dc.identifier.urihttps://doi.org/10.1111/cgf.15266
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf15266
dc.publisherEurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectvisualization
dc.subjectinformation visualization
dc.subjectvisual analytics
dc.subject• Human‐centred computing → Visualization; • Computing methodologies → Natural language processing
dc.titleNatural Language Generation for Visualizations: State of the Art, Challenges and Future Directionsen_US
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