DAQCORD – Data Access Quality & Curation for Observational Research Designs
Sharing “big, complex data” has enormous potential to enhance and accelerate biomedical research and knowledge. However, it also comes with risks, as reflected in the still commonly heard phrase “Garbage in, garbage out”. Rather than assume that data is “good” or “bad”, we propose to develop a practical self-assessment and reporting method for clinical research studies. The goal is to capture key information about data acquisition, quality control measures, and curation in a tool that is linked to the dataset so that potential research collaborators can determine if the data meets their needs and expectations. While the impetus for the consensus conference came out of the International Traumatic Brain Injury Research (InTBIR) initiative, the DAQCORD reporting system will be relevant to all large-scale studies in any health-care domain.
Read the detailed meeting notes from the Consensus Conference on Data Acquisition, Quality & Curation for Observational Research Designs (DAQCORD) Sept. 18 – 19, 2018
Data Access Quality & Curation for Observational Research Designs (DAQCORD) presentation by Dr. Ari Ercole during the International Initiative For Traumatic Brain Injury Research (InTBIR) 2019/NINDS, NIH.