Abstract
BackgroundPapers on COVID-19 are being published at a high rate and concern many different topics. Innovative tools are needed to aid researchers to find patterns in this vast amount of literature to identify subsets of interest in an automated fashion.ObjectiveWe present a new online software resource with a friendly user interface that allows users to query and interact with visual representations of relationships between publications.MethodsWe publicly released an application called PLATIPUS (Publication Literature Analysis and Text Interaction Platform for User Studies) that allows researchers to interact with literature supplied by COVIDScholar via a visual analytics platform. This tool contains standard filtering capabilities based on authors, journals, high-level categories, and various research-specific details via natural language processing and dozens of customizable visualizations that dynamically update from a researcher’s query.ResultsPLATIPUS is available online and currently links to over 100,000 publications and is still growing. This application has the potential to transform how COVID-19 researchers use public literature to enable their research.ConclusionsThe PLATIPUS application provides the end user with a variety of ways to search, filter, and visualize over 100,00 COVID-19 publications.
Highlights
COVID-19 has generated a multitude of challenges for scientific and medical researchers, but one of the unexpected challenges was the pace at which scientific literature emerged
We present a novel platform PLATIPUS (Publication Literature Analysis and Text Interaction Platform for User Studies), which builds on the comprehensive CovidScholar data set and uses visual analytics to give basic and medical researchers a more user-friendly approach to explore their queries of interest
The data in COVIDScholar includes a culmination of 19 sources, presented in Textbox 1, and consists of academic preprints, peer-reviewed research papers, book chapters, patents, clinical trial descriptions, and data sets, all of which have been made openly available by the original publishers to advance COVID-19 research
Summary
COVID-19 has generated a multitude of challenges for scientific and medical researchers, but one of the unexpected challenges was the pace at which scientific literature emerged. Computational researchers have been working diligently to assemble this information into minable collections such as CORD-19 [3], CovidScholar [4,5], and LitCovid [6,7]. These data sets are of high value but have limited interaction capabilities. We present a novel platform PLATIPUS (Publication Literature Analysis and Text Interaction Platform for User Studies), which builds on the comprehensive CovidScholar data set and uses visual analytics to give basic and medical researchers a more user-friendly approach to explore their queries of interest. Innovative tools are needed to aid researchers to find patterns in this vast amount of literature to identify subsets of interest in an automated fashion
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