The IU Network Science Institute’s partner project, the Collaborative Archive & Data Research Environment (CADRE), is making an impact with a fellowship program for researchers working on COVID-19 research.
A recent IU Research Impact article featured CADRE’s Research Cohort for the Study of Coronaviruses (RCSC), which allows researchers to take advantage of CADRE’s features and services to advance their COVID-19 related research — and the fellowship quickly took on four research teams.
RCSC researchers can access and query the COVID-19 Open Research Dataset for scholarly literature, as well as the Web of Science and Microsoft Academic Graph datasets, on the CADRE platform. Researchers will work closely with the CADRE team as they develop their work.
“The CADRE project is in a position to be able to help the scientific community, and we wanted to ensure that those resources were made available,” CADRE Director Jamie Wittenberg (IU Libraries) said in the article. “Our fellows will receive a ‘special tier’ of service including dataset access, hands-on support from our technical team and research scientists, and an opportunity to present their work to others.”
RCSC Fellow Teams
Here are the four research teams (you can also find them here):
- Filipi Nascimento Silva (Indiana University Network Science Institute) and Diego Raphael Amancio (University of São Paulo) will address the recent flood of COVID-19 studies into preprint repositories with science maps. The research team proposes a network-driven study to summarize fields related to recent COVID-19 literature.
- Sadamori Kojaku (Indiana University Bloomington) 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.
- Caroline Wagner and Xiaojing Cai (Ohio State University), Caroline V. Fry (University of Hawaii at Manoa), and Yi Zhang (University of Technology Sydney, Australia) will study the international collaboration, teaming, and science dynamics that are being created to perform COVID-19 research.
- Yulia Sevryugina (University of Michigan, Ann Arbor) will address the quality of recently published COVID-19 publications by using CADRE’s datasets to identify signs of incoherency, irreproducibility, and haste.
Are you doing work related to COVID-19 and networks at Indiana University? Let us know about it at email@example.com – we would love to highlight it here and follow your work.