Using data stories to understand spatial mental models of data in natural science domains: Characterizing technical and social infrastructure

Walkow, Samantha

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https://hdl.handle.net/2142/124253 Copy

Description

Title

Using data stories to understand spatial mental models of data in natural science domains: Characterizing technical and social infrastructure

Author(s)

Walkow, Samantha

Issue Date

2024-04-16

Director of Research (if dissertation) or Advisor (if thesis)

Turk, Matthew

Doctoral Committee Chair(s)

Turk, Matthew

Committee Member(s)

• McDowell, Kathleen
• Wickett, Karen
• Barley, William

Department of Study

Illinois Informatics Institute

Discipline

Informatics

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• mental models
• software infrastructure
• data modeling
• open source software communities
• gender in academia

Abstract

This qualitative, participatory study captures, describes, and characterizes participants' technical, social, and cognitive experiences with spatially-organized data. Participants included scientists, researchers, and software developers from a selection of natural science domains who shared how they navigated and made sense of spatially-organized data. A combination of qualitative methods was used to understand how participants conceived of large, multi-dimensional data using infrastructure. Adding to participants' cognitive load, natural science data has grown in size, quantity, and dimensionality as advances in technology allow for more data collection. A narrative mental model was found to be a common cognitive mechanism for understanding and assigning physical meaning to spatially-organized data. Data was represented and stored in many different formats, and participants applied theories from their domain, their previous experience, and software tools to map data as bits and numbers to spatially and temporally-located values. While this project focused on cognitive understanding of data work, impacts of social dynamics in academia and open source software communities surfaced through analysis. Gender differences became a salient feature as participants described vastly different experiences in their domains and larger research communities. Demonstrating that technical and social infrastructure cannot be separated, this finding traces how social and gender dynamics influenced participants' lived data experiences.

Graduation Semester

2024-05

Type of Resource

Thesis

Copyright and License Information

© 2024 Samantha Walkow

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