The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review

Abstract

Visual Analytics (VA) is a multidisciplinary field that requires various skills including but not limited to data analytics, visualizations, and the corresponding domain knowledge. Recently, many studies proposed creating and using Domain-Specific Languages (DSLs) for VA in order to abstract complexities and assist designers in developing better VAs for different data domains. However, development methods and types of DSLs vary for different applications and objectives. In this study, we conducted a systematic literature review to overview DSL methods and their intended applications for VA systems. Moreover, the review outlines the benefits and limitations of each of these methods. The aim is to provide decision support for both the research and development communities to choose the most compatible approach for their application. We think the communication of this research delivers a broad figure of previous relevant research and assists with the transfer and adaptation of the results to other domains.