A Tale of Two Models: Understanding Data Workers' Internal and External Representations of Complex Data

Fuente: arXiv
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Hauptverfasser: Scully-Allison, Connor, Williams, Katy, Brink, Stephanie, Pearce, Olga, Isaacs, Katherine E.
Format: Preprint
Veröffentlicht: 2025
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author Scully-Allison, Connor
Williams, Katy
Brink, Stephanie
Pearce, Olga
Isaacs, Katherine E.
author_facet Scully-Allison, Connor
Williams, Katy
Brink, Stephanie
Pearce, Olga
Isaacs, Katherine E.
contents Data workers may have a a different mental model of their data that the one reified in code. Understanding the organization of their data is necessary for analyzing data, be it through scripting, visualization or abstract thought. More complicated organizations, such as tables with attached hierarchies, may tax people's ability to think about and interact with data. To better understand and ultimately design for these situations, we conduct a study across a team of ten people working with the same reified data model. Through interviews and sketching, we probed their conception of the data model and developed themes through reflexive data analysis. Participants had diverse data models that differed from the reified data model, even among team members who had designed the model, resulting in parallel hazards limiting their ability to reason about the data. From these observations, we suggest potential design interventions for data analysis processes and tools.
format Preprint
id arxiv_https___arxiv_org_abs_2501_09862
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Tale of Two Models: Understanding Data Workers' Internal and External Representations of Complex Data
Scully-Allison, Connor
Williams, Katy
Brink, Stephanie
Pearce, Olga
Isaacs, Katherine E.
Human-Computer Interaction
Data workers may have a a different mental model of their data that the one reified in code. Understanding the organization of their data is necessary for analyzing data, be it through scripting, visualization or abstract thought. More complicated organizations, such as tables with attached hierarchies, may tax people's ability to think about and interact with data. To better understand and ultimately design for these situations, we conduct a study across a team of ten people working with the same reified data model. Through interviews and sketching, we probed their conception of the data model and developed themes through reflexive data analysis. Participants had diverse data models that differed from the reified data model, even among team members who had designed the model, resulting in parallel hazards limiting their ability to reason about the data. From these observations, we suggest potential design interventions for data analysis processes and tools.
title A Tale of Two Models: Understanding Data Workers' Internal and External Representations of Complex Data
topic Human-Computer Interaction
url https://arxiv.org/abs/2501.09862