In Defence of Visual Analytics Systems: Replies to Critics

Aoyu Wu, Dazhen Deng, Furui Cheng, Yingcai Wu, Shixia Liu, Huamin Qu

View presentation:2022-10-20T19:36:00ZGMT-0600Change your timezone on the schedule page
2022-10-20T19:36:00Z
Exemplar figure, described by caption below
We contribute a research on visualization research to collect data from researchers to study the underly doing of research. Specifically, we contribute two interview studies. In the first study, we asked researchers “What are the criticisms you have received during peer-reviewing?”. In the second interview, we asked researchers how to respond to those criticisms throught the research progress.

Prerecorded Talk

The live footage of the talk, including the Q&A, can be viewed on the session page, Reflecting on Academia and our Field.

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Abstract

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.