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

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Authors: Laura M. Koesten, Daphne Miedema, Hsiang‐Yun Wu, Mathias Funk
Cited by: 1
References: 54

Abstract

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.

Fields of Study & Subjects

Data Visualization and Analytics Information Systems Theories and Implementation Innovative Human-Technology Interaction

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–21
Publication date
13 April 2026
Language
EN