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

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.

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Publication Details

Published
2026-04-13
DOI
https://doi.org/10.1145/3772318.3790319
Citations
1
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Hsiang‐Yun Wu, Laura Koesten, Daphne Miedema, Mathias Funk
1 citations
Data Visualization and Analytics
article

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

Hsiang‐Yun Wu, Laura Koesten, Daphne Miedema, Mathias Funk
article en
1 citations

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.

Austrian Research Institute for Artificial Intelligence (AT), University of Applied Sciences St Pölten (AT), Mohamed bin Zayed University of Artificial Intelligence (AE), Eindhoven University of Technology (NL), University of Amsterdam (NL)
Vienna Science and Technology Fund
Openalex Percentile: Top 20%
Data Visualization and Analytics
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