Center for Large Data Research and Data Sharing in Rehabilitation (CLDR)
The Center for Large Data Research and Data Sharing in Rehabilitation (CLDR) is an extension of the previously funded, Center for Rehabilitation Research using Large Datasets. The Center continues to build scientific capacity in large data research by focusing on education and learning experiences designed to promote collaborative research. The CLDR has developed an innovative program that advances collaborative rehabilitation science research, information policy, and evidence-based rehabilitation practices.
The Center's mission is to build rehabilitation research capacity by increasing the number of investigators conducting rehabilitation and disability outcomes research using large administrative and research datasets. This mission has expanded to include an important focus on data sharing and archiving information from completed rehabilitation research studies. The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University’s Yang-Tan Institute (YTI), and the University of Michigan.
As part of CLDR, the Yang-Tan Institute has developed and maintains several tools for rehabilitation researchers, including:
Rehabilitation Dataset Directory: The Rehabilitation Dataset Directory is designed to assist rehabilitation researchers to identify potential secondary data sources. It provides basic information about large administrative and research datasets. Users can access dataset summaries including basic descriptions of each dataset and “full profile’ views that provide a wealth of additional information including sample size, population, as well as data strengths and limitations. There are also links to more documentation and information on dataset access.
Rehabilitation Research Cross-Dataset Variable Catalog: Browse or search for detailed variable level rehabilitation relevant information across 6 major datasets. The catalog provides variable names, labels, survey questions, response categories and other related variables that can be exported into an excel spreadsheet for your use. This tool is designed to provide an overview of rehabilitation-related information available across multiple datasets.
Other CLDR supported resources and collaborative opportunities:
K. Lisa Yang and Hock E. Tan Institute on Employment and Disability
ILR School, Cornell University
303A Dolgen Hall
Ithaca, NY 14853-3901
The National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineerin
University of Texas Medical Branch, ICDPSR - University of Michigan