Year: 2015
Type: article
Abstract: Starting in 2015, Opus will be the information system of record for faculty at University of California, Los Angeles (UCLA). Opus will serve as both a profile system, storing data about faculty work, and as workflow engine for the promotion and tenure process. Opus leverages institutional master data wherever possible to collect data about faculty activity. Repurposing institutional data collected for purposes not related to academic review necessitates allowing data subjects, faculty, to contextualize the data for the review process. Displaying and storing these augmented records (master data with manually added metadata from “non-authoritative” sources) has forced to project team to grapple with questions regarding fairness and transparency to both data subjects and to data consumers. How can we hold to “good design” and usability practices, while faithfully representing the inherent “messiness” of the data? How does the context in which the data was collected impact repurposing the data for academic review? This paper outlines our attempts to address these questions, noting the trade-offs and limitations of the selected solutions.
Authors: Chloe Reynolds, Heather Yvonne Small
Institution: University of California, Los Angeles
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2202489859