A Framework for the Design, Production, and Evaluation of Scientific Visualizations
Abstract
Visualizations play a critical role in discovering, understanding, interpreting, synthesizing, and communicating scientific knowledge. Effective scientific visualization requires careful attention to a number of factors, in particular, a faithful translation of scientific evidence, understanding of the communication needs of the target audience, and skillful application of visualization design principles. As a result, science visualization projects require a team of contributors with specialized knowledge and technical expertise. Regardless of team size and structure, a clear definition and appreciation of the design process as well as an understanding of the responsibilities of each contributor are imperative to the success of a project. Gaps in understanding often result in conflict between visualizers and stakeholders, compromising the quality of the scientific visualization. Although many companies have developed their own process through trial and error over years of experience, to date, there is no formalized framework for scientific visualization that details the steps of the process and the contributions of each individual. Informed by our examination of case studies, frameworks, and our collective experience as practitioners, we propose a framework tailored to the design, production, and evaluation of scientific visualization that aims to support practitioners in meeting their objectives and facilitating conversations that allow others to better understand the impact of the design process on the final product. We explore underlying drivers of decision-making within the visualization design space, describe the activities and outputs that impact decisions made about the final visualization, and discuss potential applications and limitations of this framework in practice.
K. E. Zhang, S. Saharan, G. McGill, and J. Jenkinson, A Framework for the Design, Production, and Evaluation of Scientific Visualizations, L. Shapiro, Ed., Cham: Springer Nature Switzerland, 2023. doi:10.1007/978-3-031-39035-7_7
[BibTeX]
Visualizations play a critical role in discovering, understanding, interpreting, synthesizing, and communicating scientific knowledge. Effective scientific visualization requires careful attention to a number of factors, in particular, a faithful translation of scientific evidence, understanding of the communication needs of the target audience, and skillful application of visualization design principles. As a result, science visualization projects require a team of contributors with specialized knowledge and technical expertise. Regardless of team size and structure, a clear definition and appreciation of the design process as well as an understanding of the responsibilities of each contributor are imperative to the success of a project. Gaps in understanding often result in conflict between visualizers and stakeholders, compromising the quality of the scientific visualization. Although many companies have developed their own process through trial and error over years of experience, to date, there is no formalized framework for scientific visualization that details the steps of the process and the contributions of each individual. Informed by our examination of case studies, frameworks, and our collective experience as practitioners, we propose a framework tailored to the design, production, and evaluation of scientific visualization that aims to support practitioners in meeting their objectives and facilitating conversations that allow others to better understand the impact of the design process on the final product. We explore underlying drivers of decision-making within the visualization design space, describe the activities and outputs that impact decisions made about the final visualization, and discuss potential applications and limitations of this framework in practice.
@book{zhang2023framework,
title={A Framework for the Design, Production, and Evaluation of Scientific Visualizations},
author={Zhang, Ke Er and Saharan, Shehryar and McGill, Ga{\"e}l and Jenkinson, Jodie},
editor={Shapiro, Leonard},
booktitle={Graphic Medicine, Humanizing Healthcare and Novel Approaches in Anatomical Education},
pages={131--162},
year={2023},
publisher={Springer Nature Switzerland},
address={Cham},
abstract={Visualizations play a critical role in discovering, understanding, interpreting, synthesizing, and communicating scientific knowledge. Effective scientific visualization requires careful attention to a number of factors, in particular, a faithful translation of scientific evidence, understanding of the communication needs of the target audience, and skillful application of visualization design principles. As a result, science visualization projects require a team of contributors with specialized knowledge and technical expertise. Regardless of team size and structure, a clear definition and appreciation of the design process as well as an understanding of the responsibilities of each contributor are imperative to the success of a project. Gaps in understanding often result in conflict between visualizers and stakeholders, compromising the quality of the scientific visualization. Although many companies have developed their own process through trial and error over years of experience, to date, there is no formalized framework for scientific visualization that details the steps of the process and the contributions of each individual. Informed by our examination of case studies, frameworks, and our collective experience as practitioners, we propose a framework tailored to the design, production, and evaluation of scientific visualization that aims to support practitioners in meeting their objectives and facilitating conversations that allow others to better understand the impact of the design process on the final product. We explore underlying drivers of decision-making within the visualization design space, describe the activities and outputs that impact decisions made about the final visualization, and discuss potential applications and limitations of this framework in practice.},
pdf = {pdfs/zhang2023framework.pdf},
images = {images/zhang2023framework.png},
thumbnails = {images/zhang2023frameworkthumb.png},
isbn={978-3-031-39035-7},
doi={10.1007/978-3-031-39035-7_7},
url={https://doi.org/10.1007/978-3-031-39035-7_7}
}
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