Towards Knowledge Maintenance in Scientific Digital Libraries with the Keystone Framework

• Published in: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries Vol. 2020; p. 217
• Main Authors: Fu, Yuanxi, Schneider, Jodi
• Format: Journal Article Conference Proceeding
• Language: English
• Published: United States 01.08.2020
• Subjects: argumentation theory; citation; citation of retracted papers; Knowledge maintenance; citation contexts; argument retrieval; knowledge claims; retraction of research; scientific literature
• ISSN: 1552-5996
• DOI: 10.1145/3383583.3398514

Scientific digital libraries speed dissemination of scientific publications, but also the propagation of invalid or unreliable knowledge. Although many papers with known validity problems are highly cited, no auditing process is currently available to determine whether a citing paper's findings fundamentally depend on invalid or unreliable knowledge. To address this, we introduce a new framework, the keystone framework, designed to identify when and how citing unreliable findings impacts a paper, using argumentation theory and citation context analysis. Through two pilot case studies, we demonstrate how the keystone framework can be applied to knowledge maintenance tasks for digital libraries, including addressing citations of a non-reproducible paper and identifying statements most needing validation in a high-impact paper. We identify roles for librarians, database maintainers, knowledgebase curators, and research software engineers in applying the framework to scientific digital libraries.