Collaborative Sensemaking in Visual Analytics
A literature review examining how groups notice cues, build interpretations, and act through shared analytical systems.
Sensemaking tools support more than information retrieval. They shape attention, externalize interpretations, coordinate interruptions, preserve provenance, and determine what collaborators can make common.
From cues to action
Sensemaking begins when expectations are violated or a situation becomes ambiguous. People notice cues, create interpretations, and act—learning the rules while already playing the game.
Visual-analytics systems intervene through search, filtering, extraction, categorization, evidence collection, story building, and the externalization of partial models.
Collaboration changes the loop
Shared work introduces grounding, public and private spaces, flexible ownership, coordination, interruption, provenance, and unequal access to information.
The interface must help collaborators understand not only the current conclusion, but who contributed what, how confident they were, and what changed along the way.
Gaps worth investigating
The literature concentrated on short, time-sensitive studies with limited group variation. Long-duration sensemaking, diverse and cross-functional teams, uncertainty, trust, and the unconscious work surrounding analysis remained underexplored.
These gaps point toward distributed cognition, sociomateriality, calm computing, and better distinctions between data and information as productive directions for future inquiry.
- How does a group preserve doubt instead of prematurely converging?
- When should a system interrupt collaborative analysis?
- What context must survive when an interpretation becomes a decision?