Visualization Resources: A Survey. (January 2023)

• Record Type: Journal Article
• Authors: Liu, Xiaoxiao; Alharbi, Mohammad S; Chen, Jian; Diehl, Alexandra; Rees, Dylan; Firat, Elif E; Wang, Qiru; Laramee, Robert S
• Is Part Of: Information visualization. Volume 22:Number 1(2023)
• Page Start: 3
• Page End: 30
• Publication Date: 2023-01
• Subjects: visualization technology -- visualization application -- visualization method -- visualization theory; Information visualization -- Periodicals; 006.605
• DOI: 10.1177/14738716221126992
• Languages: English
• ISSNs: 1473-8716

Abstract

Visualization, a vibrant field for researchers, practitioners, and higher educational institutions, is growing and evolving very rapidly. Tremendous progress has been made since 1987, the year often cited as the beginning of data visualization as a distinct field. As such, the number of visualization resources and the demand for those resources is increasing at a rapid pace. After a decades-equivalent long search process, we present a survey of open visualization resources for all those with an interest in interactive data visualization and visual analytics. Because the number of resources is so large, we focus on collections of resources, of which there are already many ranging from literature collections to collections of practitioner resources. Based on this, we develop a classification of visualization resource collections with a focus on the resource type, e.g. literature-based, web-based, developer focused and special topics. The result is an overview and details-on-demand of many useful resources. The collection offers a valuable jump-start for those seeking out data visualization resources from all backgrounds spanning from beginners such as students to teachers, practitioners, developers, and researchers wishing to create their own advanced or novel visual designs. This paper is a response to students and others who frequently ask for visualization resources available to them.