Exploring Interactive Linking Between Text and Visualization

Latif, Shahid; Liu, Diao; Beck, Fabian

doi:10.2312/eurovisshort.20181084

Cited by 8 publications

(7 citation statements)

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“…There has been significant research exploring how text can be leveraged and enhanced to facilitate both content consumption and creation processes. To facilitate data communication and help users efficiently synthesize information distributed across a data document, prior work has explored connecting text with other data representations (i.e., tables [4,25] and charts [29,31,54]) to enhance reading experiences, using a variety of techniques including direct manipulation, mixed-initiative, crowdsourced, and fully automatic methods. For example, Sultanum et al enabled users to specify desired links between text and charts and leveraged these text-chart links to adapt content to a range of layouts [54].…”

Section: Linking Text To Other Visual Mediamentioning

confidence: 99%

“…For example, Sultanum et al enabled users to specify desired links between text and charts and leveraged these text-chart links to adapt content to a range of layouts [54]. Latif et al developed a mixed-initiative interface by leveraging NLP techniques to construct interactive references between text and charts [31]. Kong et al developed an interactive document reading application that utilized crowdsourced links between text and charts to enable users to easily navigate from text to referred marks in a chart [29].…”

Section: Linking Text To Other Visual Mediamentioning

confidence: 99%

“…Most commercial applications do not support the creation or maintenance of text-data connections, instead requiring that users maintain these connections in their mind and perform tedious, manual updates to their documents and data. The state-of-the-art research systems that have been created to support the authoring of dynamic and interactive data documents all require the use of programming to specify data bindings [12,31], thus posing a higher barrier to entry for novice users. In addition, for each data connection, a user will need to write and update source code to specify and maintain any connections, resulting in tedious workflows, especially for data documents that contain a large amount of data.…”

Section: Introductionmentioning

confidence: 99%

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CrossData: Leveraging Text-Data Connections for Authoring Data Documents

Chen

Xia

2022

CHI Conference on Human Factors in Computing Systems

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Section: Linking Text To Other Visual Mediamentioning

confidence: 99%

Section: Linking Text To Other Visual Mediamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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CrossData: Leveraging Text-Data Connections for Authoring Data Documents

Chen

Xia

2022

CHI Conference on Human Factors in Computing Systems

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“…Similarly, Badam et al [2] proposed a web tool that relates the text to the tables and creates visualizations using these links. To reduce the effort to create interactive documents, Latif et al [22] proposed a framework for systematically generating documents that support text-visualization interaction. This system allows users to annotate the links in declarative language.…”

Section: Facilitating Reading Of Documentsmentioning

confidence: 99%

ChartText: Linking Text with Charts in Documents

Pinheiro¹,

Poco²

2022

Preprint

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Recent works show that interactive documents connecting text with visualizations facilitate reading comprehension. However, creating this type of content requires specialized knowledge. We present ChartText, a method that links text with visualizations in this work. Our approach supports documents that include bar charts, line charts, and scatter plots. ChartText receives the visual encoding of the visualization and its associated text as input. It then performs the linking in two stages: The matching stage creates individual links relating simple phrases between the text and the chart. Then, it combines the individual links according to the visual channels in the grouping stage, building more meaningful connections. We use two datasets to design and evaluate our method; the first comes from web documents (24 bar charts and texts) and the second from academic documents (25 bar charts, 25 line charts, and 25 scatter plots with their texts). Our experiments show that our method obtains F1 scores of 0.50 and 0.66 on both datasets. We can also use a semi-automatic approach correcting individual links; in this case, the scores rise to 0.68 and 0.84, respectively. To show the usefulness of our technique, we implement two proofs of concept. We create interactive documents using graphic overlays in the first one, facilitating the reading experience. We use voice instead of text to annotate charts in real-time in the second. For example, in a videoconference, our technique can automatically annotate a chart following the presenter's description.

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“…Furthermore, researchers have actively integrated visualizations and text for different purposes in different ways. Latif et al proposed a framework to produce documents supporting visualizationtext interaction by explicitly declaring links between visualizations and text in a markup language [LLB18] and developed an interactive interface to construct references between text and charts in data documents [LZK * 21]. Metoyer et al [MZJS18] presented a computational approach to generating bidirectional links between visualizations and text.…”

Section: Visualization-text Interplaymentioning

confidence: 99%

Investigating the Role and Interplay of Narrations and Animations in Data Videos

Cheng

Wang

et al. 2022

Computer Graphics Forum

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Combining data visualizations, animations, and audio narrations, data videos can increase viewer engagement and effectively communicate data stories. Due to their increasing popularity, data videos have gained growing attention from the visualization research community. However, recent research on data videos has focused on animations, lacking an understanding of narrations. In this work, we study how data videos use narrations and animations to convey information effectively. We conduct a qualitative analysis on 426 clips with visualizations extracted from 60 data videos collected from a variety of media outlets, covering a diverse array of topics. We manually label 816 sentences with 1226 semantic labels and record the composition of 2553 animations through an open coding process. We also analyze how narrations and animations coordinate with each other by assigning links between semantic labels and animations. With 937 (76.4%) semantic labels and 2503 (98.0%) animations linked, we identify four types of narration‐animation relationships in the collected clips. Drawing from the findings, we discuss study implications and future research opportunities of data videos.

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Exploring Interactive Linking Between Text and Visualization

Cited by 8 publications

References 0 publications

CrossData: Leveraging Text-Data Connections for Authoring Data Documents

CrossData: Leveraging Text-Data Connections for Authoring Data Documents

ChartText: Linking Text with Charts in Documents

Investigating the Role and Interplay of Narrations and Animations in Data Videos

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