In Defence of Visual Analytics Systems: Replies to Critics
This work provides a foundation for enhancing the scientific rigor of visual analytics research, though it is incremental as it synthesizes existing critiques rather than introducing new methods.
The authors addressed criticisms of visual analytics systems' research rigor by conducting two interview studies with researchers, identifying 36 common criticisms and gathering responses to defend and improve the field.
The last decade has witnessed many visual analytics (VA) systems that make successful applications to wide-ranging domains like urban analytics and explainable AI. However, their research rigor and contributions have been extensively challenged within the visualization community. We come in defence of VA systems by contributing two interview studies for gathering critics and responses to those criticisms. First, we interview 24 researchers to collect criticisms the review comments on their VA work. Through an iterative coding and refinement process, the interview feedback is summarized into a list of 36 common criticisms. Second, we interview 17 researchers to validate our list and collect their responses, thereby discussing implications for defending and improving the scientific values and rigor of VA systems. We highlight that the presented knowledge is deep, extensive, but also imperfect, provocative, and controversial, and thus recommend reading with an inclusive and critical eye. We hope our work can provide thoughts and foundations for conducting VA research and spark discussions to promote the research field forward more rigorously and vibrantly.