Exploring Visual Information Flows in Infographics

Lü, Min; Wang, Chufeng; Lanir, Joel; Zhao, Nanxuan; Pfister, Hanspeter; Cohen–Or, Daniel; Huang, Hui

doi:10.1145/3313831.3376263

Cited by 58 publications

(77 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The research presented in this paper is clearly limited by the number of examples we could produce and the number of interactions we could have with the participants in our design discussion and collaborative design sessions. Unlike for infographics [19,27,54], data videos [9], or data comics [14], there is no corpus that we could curate and learn from to understand best practices, or the effectiveness of existing data comics for reporting empirical studies. Our research has created an initial set of such examples, developed through design exploration and iterative collaborative design, that we make available on our website: https://statscomics.github.io.…”

Section: Limitations and Open Questionsmentioning

confidence: 99%

Data Comics for Reporting Controlled User Studies in Human-Computer Interaction

Wang

Ritchie

Zhou

et al. 2021

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

Inspired by data comics, this paper introduces a novel format for reporting controlled studies in the domain of humancomputer interaction (HCI). While many studies in HCI follow similar steps in explaining hypotheses, laying out a study design, and reporting results, many of these decisions are buried in blocks of dense scientific text. We propose leveraging data comics as study reports to provide an open and glanceable view of studies by tightly integrating text and images, illustrating design decisions and key insights visually, resulting in visual narratives that can be compelling to non-scientists and researchers alike. Use cases of data comics study reports range from illustrations for non-scientific audiences to graphical abstracts, study summaries, technical talks, textbooks, teaching, blogs, supplementary submission material, and inclusion in scientific articles. This paper provides examples of data comics study reports alongside a graphical repertoire of examples, embedded in a framework of guidelines for creating comics reports which was iterated upon and evaluated through a series of collaborative design sessions.

show abstract

Section: Limitations and Open Questionsmentioning

confidence: 99%

Data Comics for Reporting Controlled User Studies in Human-Computer Interaction

Wang

Ritchie

Zhou

et al. 2021

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

show abstract

“…The exact placement of this depends on the flow of your layout. Lu et al (2020) have constructed a map of the visual information flows for 12 of the most common infographic layouts, and referencing these maps may help you identify the location of your entry point, and the information that follows.…”

Section: Making Scientific Visualizationsmentioning

confidence: 99%

“…In Fig. 2, we used a "landscape layout," as identified in Lu et al (2020). The information flow is left-to-right, and the three panels are balanced to create symmetry, and though there is no actual narrative, the presence of the panels compels the viewer to move across the page as if there were.…”

Section: Science Visualization Examplesmentioning

confidence: 99%

Seeing science: using graphics to communicate research

Perra

Brinkman

2021

Ecosphere

View full text Add to dashboard Cite

Proper science communication is quickly becoming a professional imperative in ecology, but many researchers are not practiced in diverse and effective communication strategies. Academic jargon and text-heavy content are often cited as barriers for laypeople trying to access and understand research results. Here, we have presented scientific visualizations (infographics, figures, and illustrations) as a useful tool to reduce the information transfer gaps between researchers and the public. The graphics we have proposed are images with minimal text that convey ecological research concepts, methods, processes, and results. They are more captivating than text alone and more efficient at disseminating information to a broad audience because they reduce cognitive load. We applied tools and best practices from the fields of marketing and design to explain graphic construction and demonstrated how to build a visualization that is both aesthetic and effective. The basic principles of design are paramount to image composition, and we reviewed experimental literature to support the notions that the proper use of color, proximity, and balance helps to illuminate the main message or story that we wanted to communicate. We presented examples from wildlife ecology research in Alaska to highlight how researchers can use graphics for their own communication efforts, and emphasized the power of visual narratives to explain complex techniques and ecosystem processes. The best practices we outlined here are meant to help researchers understand the composition of science visualizations, build productive collaborations with artists, and ultimately create appealing and informative images that communicate research.

show abstract

“…Usability dimensions need to cover five things: learnability, efficiency, memorability, errors, and satisfaction. The usability test worked on five respondents, [20] stated that 5 respondents would give usability problems finding an average of 85.55 %. The first stage of measuring usability was calculating the learnability of the respondents by giving a test in the form of 2 assignments for each test.…”

Section: Usability Testingmentioning

confidence: 99%

Implementation of non-pharmaceutical intervention of COVID-19 in MRT through engineering controlled queue line using participatory ergonomics approach

Sugiono

N²,

Anggara

et al. 2021

Eureka: PE

View full text Add to dashboard Cite

The viral transmission in public places and transportations can be minimized by following the world health organization (WHO) guideline. However, the uncertainty in a dynamic system complicates the social engagement to the physical distancing regulation. This study aims to overcome this obstacle in MRT stations and train by developing an adaptive queue line system. The system was developed using low-cost hardware and open-source software to guide passengers using visual information. The system works by capturing seat images and identify the presence of humans using a cloud machine learning service. The physical representation of MRT was translated to data representation using the internet of things (IoT). The data then streamed using an asynchronous API with a representative endpoint. The endpoint is then accessed by a display computer in the destination station platform to provide visual information. The visual information was ergonomically designed with visual display principles, including the minimum content load, layout, color combination, and dimension of contents. The design of the system was evaluated by Markov simulation of virus transmission in train and usability testing of the visual design. The implementation of the system has balanced the queue line capacity in station and crowd spots distribution in MRT. The system was effective due to the visual cortex manipulation by visual information. Consequently, the aerosol and falling droplets' viral transmission radius can be reduced. Accordingly, the chance for airborne transmission can be lowered. Therefore, the adaptive queue line system is a non-pharmaceutical intervention of viral transmission diseases in public transportation

show abstract

Exploring Visual Information Flows in Infographics

Cited by 58 publications

References 22 publications

Data Comics for Reporting Controlled User Studies in Human-Computer Interaction

Data Comics for Reporting Controlled User Studies in Human-Computer Interaction

Seeing science: using graphics to communicate research

Implementation of non-pharmaceutical intervention of COVID-19 in MRT through engineering controlled queue line using participatory ergonomics approach

Contact Info

Product

Resources

About