Cronbach’s alpha indicates that as the count of items in a set increases, so does the level of relationship between them. Translational cancer research (TCR) data is an example of increasing items within a set. As a national priority, TRC is well-funded contributing to continued increase in data organizations produce, the number of organizations producing data, and the amount of sharing in which each organization participates. However, rather than leveraging the data relationships – a contextual approach – intrinsic measures such as accuracy and completeness remain referenced most often in data quality (DQ) articles and conceptual frameworks. The purpose of this set of studies is to expand our knowledge of TCR data quality (DQ) by examining context-sensitive DQ methods. The knowledge gained could be incorporated into future TCR DQ efforts, leading to more informative and actionable data, and quicker development of better clinical treatments.