A term-based and citation network-based search system for COVID-19. Issue 4 (14th December 2021)

• Record Type: Journal Article
• Authors: Zerva, Chrysoula; Taylor, Samuel; Soto, Axel J; Nguyen, Nhung T H; Ananiadou, Sophia
• Is Part Of: JAMIA open. Volume 4:Issue 4(2021)
• Publication Date: 2021-12-14
• Subjects: term extraction -- citation network -- exploratory search systems; Medical informatics -- Periodicals; 610.285
• DOI: 10.1093/jamiaopen/ooab104
• Languages: English
• ISSNs: 2574-2531

Abstract

Abstract: The COVID-19 pandemic resulted in an unprecedented production of scientific literature spanning several fields. To facilitate navigation of the scientific literature related to various aspects of the pandemic, we developed an exploratory search system. The system is based on automatically identified technical terms, document citations, and their visualization, accelerating identification of relevant documents. It offers a multi-view interactive search and navigation interface, bringing together unsupervised approaches of term extraction and citation analysis. We conducted a user evaluation with domain experts, including epidemiologists, biochemists, medicinal chemists, and medicine students. In general, most users were satisfied with the relevance and speed of the search results. More interestingly, participants mostly agreed on the capacity of the system to enable exploration and discovery of the search space using the graph visualization and filters. The system is updated on a weekly basis and it is publicly available at http://www.nactem.ac.uk/cord/ . Lay Summary: In this article, we present a search system and exploratory tool built on the documents of the COVID-19 Open Research Dataset, which is a large and open collection of scholarly articles related to COVID-19 (Coronavirus disease 2019), SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2), and related coronaviruses. The search system aims to facilitate navigation of the scientific literature related to various aspects of the pandemic. Specifically, we identify 3 types of core information per paper to be used as navigation facets including technical terminologies, citation/reference links from 1 paper to others, and bibliometric data. Unlike other exploratory-based search engines, our system allows users to combine information from text mining and bibliometrics analysis to explore the data in a more versatile manner tailored to their needs. The system is automatically updated on a weekly basis to ensure timely and updated access to recent information. We also conducted a user evaluation that included epidemiologists, biochemists, medicinal chemists, and medicine students. In general, most users were satisfied with the relevance and speed of the search results. More interestingly, participants mostly agreed on the capacity of the system to enable exploration and discovery of the search space using the graph visualization and filters.