Staring at Tables: Exploring Conceptual Data Modeling as a Rich Collaborative Activity

要旨

Conceptual data modeling is a central activity in data work, yet how such models are created remains understudied. While data attributes play a key role, modeling is also shaped by tasks, tools, developers’ prior experiences, and often unfolds collaboratively between diverse stakeholders. In this study, we invited 22 participants with varying expertise in pairs to collaboratively sketch conceptual data models. We captured screen recordings, their evolving sketches, and conversations. Through a mixed-methods approach combining thematic analysis of dialogue with an examination of model artifacts, we identify how communication and collaboration patterns influenced the process. Our findings reveal a range of collaborative strategies and representations, as well as distinct ways dialogue shaped the emergence and expression of shared conceptual models. These insights deepen understanding of Human-Data Interaction in collaborative data work and point to design opportunities for tools that better support communication, negotiation, and sensemaking of data.

著者
Laura Koesten
Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates
Daphne Miedema
University of Amsterdam, Amsterdam, Netherlands
Hsiang-Yun Wu
St. Pölten University of Applied Sciences, St. Pölten, Austria
Mathias Funk
Eindhoven University of Technology, Eindhoven, Netherlands

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Collaborative Work Systems

P1 - Room 115
7 件の発表
2026-04-14 18:00:00
2026-04-14 19:30:00