Table_2_Science Citation Knowledge Extractor.docx (806.39 kB)

Table_2_Science Citation Knowledge Extractor.docx

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posted on 18.12.2018, 13:47 by Heather Lent, Gustave Hahn-Powell, Asher Haug-Baltzell, Sean Davey, Mihai Surdeanu, Eric Lyons

The importance of academic publications is often evaluated by the number of and impact of its subsequent citing works. These citing works build upon the referenced material, representing both further intellectual insights and additional derived uses. As such, reading peer-reviewed articles which cite one's work can serve as a way for authors to understand how their research is being adopted and extended by the greater scientific community, further develop the broader impacts of their research, and even find new collaborators. Unfortunately, in today's rapidly growing and shifting scientific landscape, it is unlikely that a researcher has enough time to read through all articles citing their works, especially in the case of highly-cited broad-impact studies. To address this challenge, we developed the Science Citation Knowledge Extractor (SCKE), a web tool to provide biological and biomedical researchers with an overview of how their work is being utilized by the broader scientific community. SCKE is a web-based tool which utilizes natural language processing and machine learning to retrieve key information from scientific publications citing a given work, analyze the citing material, and present users with interactive data visualizations which illustrate how their works are contributing to greater scientific pursuits. Results are generally grouped into two categories, aimed at (1) understanding the broad scientific areas which one's work is impacting and (2) assessing the breadth and impact of one's work within these areas. As a web application, SCKE is easy to use, with a single input of PubMed ID(s) to analyze. SCKE is available for immediate use by the scientific community as a hosted web application at SCKE can also be self-hosted by taking advantage of a fully-integrated VM Image (, Docker container (, or open-source code (GPL license) available on GitHub (