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Description: This study intends to characterize the data structures and schemas that are commonly used across disciplines, and ultimately build data wrangling tools that are informed by real-world needs. We are attempting to understand the extent to which data workers utilize established concepts, the terminology they use to describe them, and common data wrangling operations that they perform. Our ultimate goal is to design free, open-source software tools that can better support data science workers in designing data abstractions. Interactive visualization of the survey dataset: https://alex-r-bigelow.github.io/wrangling-survey/Responses.html For the first publication's archive of codes, themes, and associated audit, see the child OSF component: https://osf.io/382fn/

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Guidelines For Pursuing Latent Data Abstractions

InfoVis 2020 Submission, with supplemental archive of codes, themes, and their associated audit. For the archived survey results, see the parent proj...

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