A term-based and citation network-based search system for COVID-19

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/.

Model-based Engineering and the Digital Thread

“…The issue of unstructured data is still one of the lesser-mentioned tricky problems in the world of digital thread and twin. We are reaching out to the bleeding edge in this area to overcome the ontological and structural hurdles, and take inspiration from successes in parallel fields, such as progress by researchers working in the biomedical field at the University of Manchester (Zerva et al, 2021). And we are actively working to develop technologies and techniques to exploit graph technologies and manage the evolution of enterprise semantics over time.…”