Abstract
As scientists worldwide search for answers to the overwhelmingly unknown behind the deadly pandemic, the literature concerning COVID-19 has been growing exponentially. Keeping abreast of the body of literature at such a rapidly advancing pace poses significant challenges not only to active researchers but also to society as a whole. Although numerous data resources have been made openly available, the analytic and synthetic process that is essential in effectively navigating through the vast amount of information with heightened levels of uncertainty remains a significant bottleneck. We introduce a generic method that facilitates the data collection and sense-making process when dealing with a rapidly growing landscape of a research domain such as COVID-19 at multiple levels of granularity. The method integrates the analysis of structural and temporal patterns in scholarly publications with the delineation of thematic concentrations and the types of uncertainties that may offer additional insights into the complexity of the unknown. We demonstrate the application of the method in a study of the COVID-19 literature.
Highlights
The COVID-19 pandemic has impacted so many people’s everyday life worldwide and it is still threatening our society as a whole
To demonstrate the application of this integrated and enhanced method, we focus on the COVID-19 literature
At Level 3, we demonstrate the application of the predictive Structural Variation Analysis (SVA) procedure to the dataset and identify a set of newly published articles that may be too young to stand out in terms of their citation counts but start to show signs of transformative potential
Summary
The COVID-19 pandemic has impacted so many people’s everyday life worldwide and it is still threatening our society as a whole. The COVID-19 pandemic is unprecedented in several ways that make it challenging and threatening: it is still largely unknown of its origin and transmission routes; there may be months or even longer before COVID-19 vaccines can be expected to be a powerful line of defense; and the prolonged pandemic continues to pose social, economic, and political challenges to businesses and entire industries such as airlines and international travel as well as schools and many other areas. Scientists and researchers have actively responded to the urgency and severity of the pandemic. Publications relevant to COVID-19 have increased rapidly across disciplines since the beginning of 2020. Several institutions and corporate organizations have contributed openly accessible datasets of COVID-19 publications, notably including the CORD-19 dataset and the Lens. The COVID-19 Open Research Dataset (CORD-19) covers the scholarly literature of COVID-19, SARS-CoV-2, and the coronavirus group.
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