Searching for scientific evidence in a pandemic: An overview of TREC-COVID

Kirk Roberts, Tasmeer Alam, Steven Bedrick, Dina Demner-Fushman, Kyle Lo, Ian Soboroff, Ellen M. Voorhees, Lucy Lu Wang, William R. Hersh

Abstract: Highlights • TREC-COVID Information Retrieval (IR) shared task, developed in response to the COVID-19 pandemic. • Differs from most IR shared tasks (multi-round, short turnaround, residual judgments, feedback). • Significant participation in the task, including 92 unique teams and 556 total submissions. • Final test collection contains 50 topics with 69,318 manual judgments on the CORD-19 corpus. Abstract We present an overview of the TREC-COVID Challenge, an information retrieval (IR) shared task to evaluate search on scientific literature related to COVID-19. The goals of TREC-COVID include the construction of a pandemic search test collection and the evaluation of IR methods for COVID-19. The challenge was conducted over five rounds from April to July 2020, with participation from 92 unique teams and 556 individual submissions. A total of 50 topics (sets of related queries) were used in the evaluation, starting at 30 topics for Round 1 and adding 5 new topics per round to target emerging topics at that state of the still-emerging pandemic. This paper provides a comprehensive overview of the structure and results of TREC-COVID. Specifically, the paper provides details on the background, task structure, topic structure, corpus, participation, pooling, assessment, judgments, results, top-performing systems, lessons learned, and benchmark datasets.