Data Collection and Quality Assurance

Once you have conceptualized the kind of question you would like to answer and understand the type of data you would need to achieve your research goals, you need to collect the data. You can collect data of many forms using many different resources, platforms, and tools.

Data Collection Resources

Survey Data

Research Database Creation (REDCap)

Digital Data Collection

Quality Assurance

As data is being collected, it is important to conduct Quality Assurance (QA) to define the expected standards, such as data formats, codes, metadata and conduct Quality Control (QC) so that specific checks and tests are in place to detect poor quality data and address them through correction or appropriate documentation.

NIH Guidelines: https://www.ninds.nih.gov/current-research/research-funded-ninds/clinical-research/quality-assurance-guidelines

Johns Hopkins Institute for Clinical and Translational Research (ICTR) Best Practices for Research Data Management - Quality Assurance/Quality Control