Evaluation of Interactive Data Visualization Tools Based on Gaze and Mouse Tracking

Peng, Chiu-Fang; Liao, Wen‐Hung

doi:10.1109/ism.2016.0099

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…When researching a method to evaluate software, the authors found no articles evaluating visualization tools with a rubric. Usability studies and tracking technologies have been used to assess data visualization tools and techniques to provide feedback to designers (for example: Peng and Liao 2017;Li and North 2003;Ren et al 2012); studies have evaluated the visualization capabilities of given tools (for example: Sopan et al 2012); discipline-specific demonstrations of the effectiveness of data visualization techniques have been reported (for example: Cui et al 2016;Boluri et al 2016). However, a standard rubric to evaluate and compare general purpose data visualization tools from a user's perspective was not found in the literature.…”

Section: Literature Reviewmentioning

confidence: 99%

Using the Visualization Software Evaluation Rubric to explore six freely available visualization applications

Atwood¹,

Reznik-Zellen²

2018

JeSLIB

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Objective: As a variety of visualization tools become available to librarians and researchers, it can be challenging to select a tool that is robust and flexible enough to provide the desired visualization outcomes for work or personal use. In this article, the authors provide guidance on several freely available tools, and offer a rubric for use in evaluating visualization tools. Methods: A rubric was generated to assist the authors in assessing the selected six freely available visualization tools. Each author analyzed three tools, and discussed the differences, similarities, challenges, and successes of each. Results: Of the six visualization tools, two tools emerged with high marks. The authors found that the rubric was a successful evaluation tool, and facilitated discussion on the strengths and weaknesses of the six selected visualization pieces of software. Conclusions: Of the six different visualization tools analyzed, all had different functions and features available to best meet the needs of users. In a situation where there are many options available, and it is difficult at first glance to determine a clear winner, a rubric can be useful in providing a method to quickly assess and communicate the effectiveness of a tool.

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Section: Literature Reviewmentioning

confidence: 99%

Using the Visualization Software Evaluation Rubric to explore six freely available visualization applications

Atwood¹,

Reznik-Zellen²

2018

JeSLIB

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“…As avaliações de UX podem ser realizadas por meio de diferentes técnicas e metodologias, como questionários [13], expressões faciais [8], rastreamento de cursor do mouse (mouse tracking) e do movimento dos olhos (eye tracking) [10], entre outros. As avaliações de UX objetivam avançar no sentido de desenvolver bens e serviços centrados no usuário [11].…”

Section: Introductionunclassified

UX-Tracking: Web and Multimodal Tool for User Experience Evaluation

Lima¹,

Moura²,

Alves³

et al. 2022

Anais Estendidos Do XXVIII Simpósio Brasileiro De Sistemas Multimídia E Web (WebMedia 2022)

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Different markets have increasingly sought to offer personalized experiences in the use of their products and/or services. From that, this work presents UX-Tracking, a web tool for multimodal capture that adds a set of tracking techniques to allow User Experience (UX) evaluation. UX-Tracking allows you to simultaneously track mouse, eye, keyboard, history and, in the future, voice data in a single session with the user. This factor contributes to greater accuracy in UX assessments, since the interaction can be analyzed from different perspectives. As such, UX-Tranking is expected to be an alternative for researchers and professionals from academia and industry to improve quality of interaction with products and services in digital interfaces accessed via a web browser.

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Investigating Viewer’s Reliance on Captions Based on Gaze Information

Liao

Chen

2021

Artificial Intelligence in HCI

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Evaluation of Interactive Data Visualization Tools Based on Gaze and Mouse Tracking

Cited by 4 publications

References 8 publications

Using the Visualization Software Evaluation Rubric to explore six freely available visualization applications

Using the Visualization Software Evaluation Rubric to explore six freely available visualization applications

UX-Tracking: Web and Multimodal Tool for User Experience Evaluation

Investigating Viewer’s Reliance on Captions Based on Gaze Information

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