RCSC Program

We have received a lot of interest in this program and have recently taken on four new fellowship teams. While we want to support as many RCSC research projects as possible, we have put a pause on accepting new fellows until we have the capacity to provide intensive support for new teams. You are welcome to submit a prospoal to be considered at a future date. You are also welcome to access CADRE's Microsoft Academic Graph dataset during our alpha phase. Learn more.

In response to the White House's call to action for the scientific community to help answer COVID-19 questions with the COVID-19 Open Research Dataset (CORD-19) of scholarly literature, the CADRE project has opened a special fellowship program for researchers who are working on coronavirus-related research.

These researchers can take advantage of a special tier of service through CADRE's new Research Cohort for the Study of Coronaviruses Program (RCSC). Please note, fellows will lose access to the Web of Science dataset if they leave the institution they applied to the RCSC Program with.

As an RCSC researcher, you can:

All of this can be done in CADRE's cloud-based platform.

Additional details

Applicants can form research teams consisting of graduate students, staff, and faculty from any U.S. or non-U.S. university—and teams can span any discipline and institution. You may also submit a research proposal without a team.

If you have any questions, you can contact us.

External resources

The CADRE Project also wants to highlight important resources researchers can take advantage of during this time.

Current RCSC Researchers

Science maps of research referenced in COVID-19 articles from the Indiana University Network Science Institute and the University of São Paulo

These researchers plan to address the recent flood of COVID-19 studies into preprint repositories. The sudden influx makes it difficult for researchers to stay on top of research that is relevant to their particular field using metrics or citations. The research team proposes a network-driven study that summarizes the fields related to recent COVID-19 literature. They will accomplish this by building citation networks among the most recent studies and applying community detection and keyword extraction to understand how the literature is organized. The researchers say that automated methods for summarizing COVID-19 research, as well as interactive visualizations, will aid other researchers in finding the most relevant and recent research in their field. The team will use CADRE's unified environment for access to scholarly datasets to accelerate their research.

Creating a map of COVID-19 research using neural embeddings: A retrospective approach from Indiana University Bloomington

This project will create a map of papers on COVID-19 that will be compared with maps for similar viruses, such as SARS and influenza, to better understand unexplored and concentration areas in the research. Kojaku will employ neural embedding methods, used to project research papers onto a low dimensional space using citations and semantic information, and then compare the density of papers on COVID-19 with other diseases. Kojaku says this research will both address unexplored areas that may deserve more attention and allow researchers to easily explore research related to COVID-19. Kojaku is part of the Science Genome project, which is a close CADRE collaborator, and says he will use CADRE to access the comprehensive, continuously updated CORD-19 dataset and related research, as well as to receive support from CADRE’s technical team and access to its computing resources.

Tracking and Recognizing Patterns of Communication, Search, and International Collaboration in COVID-19 Research from Ohio State University, University of Hawaii at Manoa, and University of Technology Sydney

This research team plans to study the international collaborations that are forming to perform COVID-19 research. The researchers say the combination of an intense research focus and a demand for quick results provides a rare opportunity for social scientists who study collaboration, teaming, and science dynamics. The team added that the abundant informal communications and knowledge sharing among scientists to address COVID-19 is rare. All of these circumstances have created an opportunity for the researchers to study team formations in real-time with CADRE. They plan to take advantage of CADRE’s datasets and technical team for their research. Two team mebers (Wagner and Cai) are also currently using CADRE for another CADRE Fellowship project.

Study of Pandemic Publishing: How Scholarly Literature is Affected by COVID-19 Pandemic from the University of Michigan

Yulia Sevryugina’s project will address the quality of recently published COVID-19 publications. Sevryugina says COVID-19 related research is being performed and published hastily. She adds that turnaround times for medical journal publications have decreased by almost 50 percent. Speedy research and condensed publication timelines contribute to a lack of scientific rigor and increase the likelihood of corrections and retractions, leading to the spread of false information in trusted journals. Sevryugina will study the quality of COVID-19 related scholarly works by using CADRE’s datasets to identify signs of incoherency, irreproducibility, and haste. That includes analyzing COVID-19 published literature for incoherent writing, stylistic errors, plagiarism, speculative language, unreproducible experiments, and far-fetched conclusions based on poor quality data. She will also examine retracted and corrected manuscripts and explore their citation maps to understand how errors propagate through scholarly literature. Sevryugina hopes her research will help others find the balance between expediting publication timelines and maintaining research quality.