This study examines how a data platform intermediary enables the evolution of viscous data into liquid data. Viscous, or difficult to use, data is the result of data usage problems that often plague information systems. Data may be viscous because of poor quality, staleness, size issues, unusable formats, missing metadata, unknown history, mysterious provenance, poor access for users, and inability to move data between systems. Viscous data is problematic to use and difficult to incorporate into decision making. On the other hand, liquid data is high quality, formatted to be machine-readable, has provenance and metadata, is easy to move in and out of different systems, is accessible by users, and lends itself well to being used for decision making. Using a longitudinal case study that follows a data platform intermediary startup company from late 2015 to 2018, I break down elements of the platform into data users, data providers, and data intermediaries. Using a lens from the Community of Practice literature, I show how social learning, data wrangling, data complementing, and data liberalizing on a digital data platform transform data from viscous to liquid. This work contributes by providing a different perspective to data management, a means to address a dearth of data skills, and a way to make data more usable for both individuals and institutions.
|Advisor:||Leidner, Dorothy E.|
|Commitee:||Trower, Jonathan, Burleson, Debra, Kayworth, Timothy, Klein, Peter|
|School Location:||United States -- Texas|
|Source:||DAI-B 81/2(E), Dissertation Abstracts International|
|Keywords:||Open data, Data platforms, Digital platforms, Data scientists|
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