Optimizing Visual Analytics Workflows: From Theory to Practice

2026-06-23

AI Summary

This study addresses the systematic challenge of integrating human-centered and machine-centered processes in visual analytics workflows by proposing an information-theoretic ontological approach. Through action research and multi-domain case studies, it demonstrates for the first time the feasibility of theory-driven optimization in real-world settings and identifies key barriers limiting its broader adoption. The work clarifies both the strengths and limitations of this approach, fosters consensus within the field, and articulates a practical roadmap to facilitate its implementation. By doing so, it provides both theoretical grounding and actionable guidance for the co-design of visual analytics systems.

Abstract

The principle of visual analytics (VA) is to provide integrated workflows where human-centric processes (e.g., visualization and interaction) and machine-centric processes (e.g., statistics and algorithms) complement each other. To implement this principle in practice, it is necessary to reason about the trade-offs among different processes and make optimal use of them in a workflow. Building on an existing ontology of the methodology for analyzing such trade-offs information-theoretically and for optimizing VA workflows systematically, we investigate ways to transform this methodology from theory to practice. In particular, we adopted the action research method. Through case studies in different application domains, VA researchers with different background knowledge and experiences offered their answers to several hypotheses about using the methodology in practice and proposed ways forward. In this paper, we present our collective analysis, the strengths and feasibility of this theory-based methodology, as well as the obstacles to its broad deployment in practice. To address these challenges, we outline a roadmap to remove such obstacles.

Problem

• visual analytics
• workflow optimization
• human-machine collaboration
• theory-to-practice
• action research

Innovation

• visual analytics
• workflow optimization
• information-theoretic methodology
• action research
• human-machine collaboration