A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance

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Hauptverfasser: Monadjemi, Shayan, Guo, Yuhan, Xu, Kai, Endert, Alex, Crisan, Anamaria
Format: Preprint
Veröffentlicht: 2025
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author Monadjemi, Shayan
Guo, Yuhan
Xu, Kai
Endert, Alex
Crisan, Anamaria
author_facet Monadjemi, Shayan
Guo, Yuhan
Xu, Kai
Endert, Alex
Crisan, Anamaria
contents Artificial agents are increasingly integrated into data analysis workflows, carrying out tasks that were primarily done by humans. Our research explores how the introduction of automation re-calibrates the dynamic between humans and automating technology. To explore this question, we conducted a scoping review encompassing twenty years of mixed-initiative visual analytic systems. To describe and contrast the relationship between humans and automation, we developed an integrated taxonomy to delineate the objectives of these mixed-initiative visual analytics tools, how much automation they support, and the assumed roles of humans. Here, we describe our qualitative approach of integrating existing theoretical frameworks with new codes we developed. Our analysis shows that the visualization research literature lacks consensus on the definition of mixed-initiative systems and explores a limited potential of the collaborative interaction landscape between people and automation. Our research provides a scaffold to advance the discussion of human-AI collaboration during visual data analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2509_19152
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance
Monadjemi, Shayan
Guo, Yuhan
Xu, Kai
Endert, Alex
Crisan, Anamaria
Human-Computer Interaction
Artificial agents are increasingly integrated into data analysis workflows, carrying out tasks that were primarily done by humans. Our research explores how the introduction of automation re-calibrates the dynamic between humans and automating technology. To explore this question, we conducted a scoping review encompassing twenty years of mixed-initiative visual analytic systems. To describe and contrast the relationship between humans and automation, we developed an integrated taxonomy to delineate the objectives of these mixed-initiative visual analytics tools, how much automation they support, and the assumed roles of humans. Here, we describe our qualitative approach of integrating existing theoretical frameworks with new codes we developed. Our analysis shows that the visualization research literature lacks consensus on the definition of mixed-initiative systems and explores a limited potential of the collaborative interaction landscape between people and automation. Our research provides a scaffold to advance the discussion of human-AI collaboration during visual data analysis.
title A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance
topic Human-Computer Interaction
url https://arxiv.org/abs/2509.19152