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1. COVID-view: Diagnosis of COVID-19 using Chest CT

   https://doi.org/10.1109/TVCG.2021.3114851  

   Jadhav, S.; Deng, G.; Zawin, M.; Kaufman, A. (January 2022, IEEE transactions on visualization and computer graphics)
2. Remembering COVID-19

   https://doi.org/10.1353/sor.2020.0028  

   Hirst, William (June 2020, Social Research: An International Quarterly)
3. COVID‐19 and cybersecurity

   https://doi.org/10.1049/ise2.12084  

   Di Pietro, Roberto; Trieu, Ni; Iovino, Vincenzo (January 2022, IET information security)
4. COVID information commons archive

   https://doi.org/10.5061/dryad.37pvmcvqp  

   Hudson, Florence D; Scherle, Ryan; Close, Lauren; Mahajan, Varalika; Sango, Benjamin; Yang, Helen; Stewart, Haleigh; Johnson, Sven; Ragnauth, Karl; Naum, Katie; et al (February 2024, Dryad)

   The COVID Information Commons (CIC) is an open website portal and community to facilitate knowledge-sharing and collaboration across various COVID research efforts, funded by the NSF Convergence Accelerator and the  NSF Technology, Innovation and Partnerships Directorate. The CIC serves as an open resource for researchers, students, and decision-makers from academia, government, not-for-profits and industry to identify collaboration opportunities, to leverage each other's research findings, and to accelerate the most promising research to mitigate the broad societal impacts of the COVID-19 pandemic. The CIC was developed as a collaborative proposal led by the Northeast Big Data Innovation Hub, hosted by Columbia University, in collaboration with the Midwest Big Data Innovation Hub, South Big Data Innovation Hub, and West Big Data Innovation Hub.  It was funded by the NSF Convergence Accelerator (NSF #2028999) in May  2020 and launched in July 2020.  The initial focus of the CIC website was on the 723 NSF-funded COVID Rapid Response Research (RAPID) projects funded in 2020. The CIC-E: COVID Information Commons Extension for Pandemic Recovery project was proposed and funded in 2021 (NSF #2139391) by the CIC project team with the goal to increase researcher collaboration across NSF and NIH awardees and with global collaborators, as we continue to combat the novel coronavirus, and glean learnings for future uses of innovations developed for COVID response and recovery, including potential insights which can be leveraged for future pandemics. The CIC extension launched on June 30, 2022 increasing the corpus of awards from just NSF to include NIH-funded COVID related awards, both present and past, through all funding vehicles, in pertinent areas of COVID research, response and recovery. The CIC-extension provides more opportunity for multi-agency and multidisciplinary research collaboration as all the Principal Investigators (PIs) for awards in the CIC are invited to present their research and collaborate on CIC Research Lighting Talk Webinars and Collaboration Sessions. The COVID Information Commons (CIC) archive in Dryad includes the NSF and NIH COVID-related awards in the CIC, as well as links to valuable COVID-related datasets, groups, guides and artifacts including videos and transcripts of the CIC researcher lightning talks. The CIC archive was created in Dryad in 2024 at 84.24 MB and is updated annually. The 2025 update to the CIC archive in Dryad is 91.94 MB. It can be cited as follows: Hudson, Florence et al. (2024). COVID information commons archive [Dataset]. Dryad. https://doi.org/10.5061/dryad.37pvmcvqp 

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5. The long COVID research literature

   https://doi.org/10.3389/frma.2023.1149091  

   Porter, Alan L.; Markley, Mark; Newman, Nils (March 2023, Frontiers in Research Metrics and Analytics)

   While the COVID-19 pandemic morphs into less malignant forms, the virus has spawned a series of poorly understood, post-infection symptoms with staggering ramifications, i. e., long COVID (LC). This bibliometric study profiles the rapidly growing LC research domain [5,243 articles from PubMed and Web of Science (WoS)] to make its knowledge content more accessible. The article addresses What? Where? Who? and When? questions. A 13-topic Concept Grid presents bottom-up topic clusters. We break out those topics with other data fields, including disciplinary concentrations, topical details, and information on research “players” (countries, institutions, and authors) engaging in those topics. We provide access to results via a Dashboard website. We find a strongly growing, multidisciplinary LC research domain. That domain appears tightly connected based on shared research knowledge. However, we also observe notable concentrations of research activity in different disciplines. Data trends over 3 years of LC research suggest heightened attention to psychological and neurodegenerative symptoms, fatigue, and pulmonary involvement. 

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