Situatedness in Visualization Design: Making Unresolved Work Actionable

Authors

Paul C Parsons (Purdue University), Prakash Chandra Shukla (Purdue University), Phuong Bui (Purdue University), Srishti Agrawal (Purdue University), Ali Baigelenov (Purdue University)

Presentation

Session

The more the merrier

Time

Tuesday, Nov 10, 10:00 – 10:12 (US/Eastern) · session 10:00 – 11:30

Location

Hall America north

Keywords

Visualization design, situated action, professional practice

Abstract

Visualization design often proceeds under unresolved conditions---goals shift, data remain provisional, stakeholder needs evolve, and several plausible directions may remain available at once. Existing visualization frameworks help organize design work and articulate major decisions, yet offer limited explanation of how practitioners proceed before a path forward has become clear. Drawing on an episode-level analysis of a previously collected three-phase qualitative corpus involving eleven expert visualization practitioners, we examine situations in which the problem, representational target, or viable direction remained unsettled. We find that practitioners make such situations actionable through provisional local moves. These moves reveal patterns, distinctions, and interpretive possibilities; clarify what is tractable, viable, or worth pursuing; and sometimes reorient the work itself. The analysis shows that situated action, professional judgment, and explicit design reasoning are intertwined in expert practice. It also identifies a practical limit on how fully design activity can be specified in advance. When the meaning of the next move depends on what a situation reveals in response to action, prescriptive decision structures cannot fully determine the course of design. The paper contributes an empirical account of situatedness in visualization practice and explains how local action makes unresolved work interpretable enough for consequential design decisions.

For Practitioners

The paper will be most relevant to practitioners who design visualizations under open-ended or changing conditions, including data visualization designers and developers, data journalists, information and UX designers, visualization consultants, and data analysts or data scientists who create visual representations for exploration, communication, or decision support. It may also interest design leads and developers of visualization or AI-assisted design tools. Practitioners can use the paper as a conceptual framework for recognizing and responding to situations in which the problem, data, stakeholder requirements, or representational direction has not yet stabilized. Rather than forcing an early decision, they can use provisional actions—such as restructuring data, sketching partial views, testing an encoding, narrowing scope, or constructing a quick prototype—to discover consequential patterns or determine what is feasible. The findings also help practitioners distinguish productive reorientation from routine refinement and recognize that fallback, simplification, and feasibility testing are substantive forms of design reasoning. Applied in practice, this perspective can help teams avoid premature closure, communicate why a project’s direction has changed, and select methods or tools that expose the consequences of tentative moves while leaving room for the situation to develop.