Examining interaction techniques in data visualization authoring tools from the perspective of goals and human cognition: a survey

Rubab, Sadia; Tang, Junxiu; Wu, Yingcai

doi:10.1007/s12650-020-00705-3

Cited by 8 publications

(3 citation statements)

References 77 publications

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“…Data visualization includes not only the field of information visualization but also the field of scientific visualization. Data visualization is the visual interpretation of data through modeling, image, animation, and other forms using computer visual image processing [19][20][21]. Visualization is a display method that transforms abstract things or programs into charts or images.…”

Section: Data Visualization Technologymentioning

confidence: 99%

Visual Dynamic Simulation Model of Unstructured Data in Social Networks

Zhang

2022

Security and Communication Networks

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Social networks contain a large amount of unstructured data. To ensure the stability of unstructured big data, this study proposes a method for visual dynamic simulation model of unstructured data in social networks. This study uses the Hadoop platform and data visualization technology to establish a univariate linear regression model according to the time correlation between data, estimates and approximates perceptual data, and collects unstructured data of social networks. Then, the unstructured data collected from the original social network are processed, and an adaptive threshold is designed to filter out the influence of noise. The unstructured data of social network after feature analysis are processed to extract its visual features. Finally, this study carries out the Hadoop cluster design, implements data persistence by HDFS, uses MapReduce to extract data clusters for distributed computing, builds a visual dynamic simulation model of unstructured data in social network, and realizes the display of unstructured data in social network. The experimental results show that this method has a good visualization effect on unstructured data in social networks and can effectively improve the stability and efficiency of unstructured data visualization in social networks.

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Section: Data Visualization Technologymentioning

confidence: 99%

Visual Dynamic Simulation Model of Unstructured Data in Social Networks

Zhang

2022

Security and Communication Networks

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“…Although an automatic system provides convenience, the generated visualization may not satisfy users' expectations. Therefore, users should engage in the creation process [53]. We consider a mixed-initiative workflow that integrates the machine's and human being's efforts.…”

Section: Design Considerationsmentioning

confidence: 99%

MetaGlyph: Automatic Generation of Metaphoric Glyph-based Visualization

Lü

Shu

Deng

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. Example MGVs generated by MetaGlyph: (a) several attributes of different pokemons; (b) forest area changes in different countries from 1995 to 2020; (c) display of various CDs; (e) multiple hotels' information arranged by price (x) and rate (y); (f) chocolates in different ratings placed on a map; (g) disparate mushrooms. The legends in (a1)(b1)(f1) are also generated by MetaGlyph. The center boxes with yellow backgrounds illustrate the data mappings for each glyph. Encoding channels are represented in icons and (d) shows the annotation. Dashed arrows are used to associate visual elements with the resulting visualizations.

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“…Rosli and Cabrera [RC15], for example, have identified the potential of integrated designs to form a more concise, general representation of the data set compared to individual stimuli alone. Rubab et al recently explored relationships between auditory channels and visual channels and suggested factors that impact their effectiveness [RYTW23].…”

Section: Introductionmentioning

confidence: 99%

Open Your Ears and Take a Look: A State‐of‐the‐Art Report on the Integration of Sonification and Visualization

Enge,

Elmquist,

Caiola

et al. 2024

Computer Graphics Forum

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The research communities studying visualization and sonification for data display and analysis share exceptionally similar goals, essentially making data of any kind interpretable to humans. One community does so by using visual representations of data, and the other community employs auditory (non‐speech) representations of data. While the two communities have a lot in common, they developed mostly in parallel over the course of the last few decades. With this STAR, we discuss a collection of work that bridges the borders of the two communities, hence a collection of work that aims to integrate the two techniques into one form of audiovisual display, which we argue to be “more than the sum of the two.” We introduce and motivate a classification system applicable to such audiovisual displays and categorize a corpus of 57 academic publications that appeared between 2011 and 2023 in categories such as reading level, dataset type, or evaluation system, to mention a few. The corpus also enables a meta‐analysis of the field, including regularly occurring design patterns such as type of visualization and sonification techniques, or the use of visual and auditory channels, showing an overall diverse field with different designs. An analysis of a co‐author network of the field shows individual teams without many interconnections. The body of work covered in this STAR also relates to three adjacent topics: audiovisual monitoring, accessibility, and audiovisual data art. These three topics are discussed individually in addition to the systematically conducted part of this research. The findings of this report may be used by researchers from both fields to understand the potentials and challenges of such integrated designs while hopefully inspiring them to collaborate with experts from the respective other field.

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Examining interaction techniques in data visualization authoring tools from the perspective of goals and human cognition: a survey

Cited by 8 publications

References 77 publications

Visual Dynamic Simulation Model of Unstructured Data in Social Networks

Visual Dynamic Simulation Model of Unstructured Data in Social Networks

MetaGlyph: Automatic Generation of Metaphoric Glyph-based Visualization

Open Your Ears and Take a Look: A State‐of‐the‐Art Report on the Integration of Sonification and Visualization

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