Data Catalog

Portal to COVID-19-related pre-prints, datasets, presentations, and software housed in the Figshare research repository.

Researchers, students, and others in the Models of Infectious Disease Agent Study (MIDAS) create and use computational models to study transmission dynamics of a broad range of infectious diseases. Many MIDAS members are conducting research on COVID-19 and are contributing to an extraordinary international collection of data and information regarding the outbreak. Through its Online Portal for COVID-19 Modeling Research, MIDAS provides access to COVID-19-related data and parameter estimates as well as a software catalog with a list of dashboards and visualizations for following the COVID-19 pandemic.

The COVID-19 Open Research Dataset is an extensive machine-readable resource of over 45,000 scholarly articles, including over 33,000 with full text, about COVID-19 and the coronavirus family of viruses for use by the global research community. This dataset is intended to mobilize researchers to apply recent advances in natural language processing to generate new insights in support of the fight against this infectious disease. The dataset is updated weekly and contains all COVID-19 and coronavirus-related research (e.g., SARS, MERS) from the following sources: PubMed's PMC open access corpus (using this query: COVID-19 and coronavirus research), additional COVID-19 research articles from a corpus maintained by the World Health Organization (WHO), and bioRxiv and medRxiv pre-prints (using this query: COVID-19 and coronavirus research). Also available is a comprehensive metadata file of 44,000 coronavirus and COVID-19 research articles with links to PubMed, Microsoft Academic, and the WHO COVID-19 database of publications (includes articles without open access full text).

An extensible, scalable informatics platform for traumatic brain injury (TBI) relevant data (including medical imaging, clinical assessment, environmental and behavioral history, etc.) and for all data types (text, numeric, image, time series, etc.). FITBIR is sponsored by the U.S. Army Medical Research and Materiel Command (USAMRMC) and supported by the National Institutes of Health National Institute of Neurological Disorders and Stroke (NINDS) and Center for Information Technology (CIT).

To determine the overall quality of Data Management Plans (DMPs) at Wayne State University, the Library System’s Research Data Services (RDS) team evaluated the content of 119 DMPs from grant proposals submitted to the National Science Foundation by Wayne State University researchers between 2012 and 2014. The DMPs were evaluated using a 15-question modified rubric previously used by researchers at University of Michigan.

The State Ambulatory Surgery and Services Databases (SASD) are State-specific files that include data for ambulatory surgery and other outpatient services from hospital-owned facilities. In addition, some States provide ambulatory surgery and outpatient services from nonhospital-owned facilities. The uniform format of the SASD helps facilitate cross-State comparisons. The SASD are well suited for research that requires complete enumeration of hospital-based ambulatory surgeries within geographic areas or States.

The COVID Racial Data Tracker is a collaboration between the COVID Tracking Project and the Antiracist Research & Policy Center. This team tracks race and ethnicity data from every state that reports it, and is updated twice per week.

The Surveillance, Epidemiology, and End Results (SEER) Program provides information on cancer statistics in an effort to reduce the cancer burden among the U.S. population. SEER is supported by the Surveillance Research Program (SRP) in NCI's Division of Cancer Control and Population Sciences (DCCPS).

The National Institutes of Health (NIH) Data Book (NDB) provides basic summary statistics on extramural grants and contract awards, grant applications, the organizations that NIH supports, the trainees and fellows supported through NIH programs, and the national biomedical workforce. The Data Book is organized into categories and sub-categories, each of which will display related reports together on a single page. Most reports provide both an interactive chart visualization and the underlying data table.

Interactive visualizations of Wayne State University data on student enrollment (by college, class level, full/part time status, race/ethnicity, and gender), degree completion (by college/department/major, race/ethnicity, STEM vs. non-STEM), faculty and staff count (by college, EEO category, tenure status, race/ethnicity, and gender), finance (budget by revenue source, account pool group, program, and college) research (number of awards and total dollar amount by sponsor), and development (gifts recorded and pledges received).