Organizing research data for effective analysis has been insufficiently addressed in the methodological literature. This article proposes that concepts of knowledge organization relating to relevance, precision, recall, coextensiveness, exhaustivity, specificity, and consistency offer a ready-made model that can be applied to research data. The knowledge organization (KO) model is reinterpreted for transferability to quantitative, qualitative, and textual research. In each instance, the model's applicability is illustrated with examples from the authors' research. This exploration demonstrates the model's resiliency in organizing numeric data, coding transcripts, and marking up textual statements. The limitations of the model are noted and compromises are described, providing a valuable approach to meaningful data preparation for researchers, educators, students, and reviewers of research across disciplines. The article concludes that the KO model contributes significantly to the ability of researchers to collect and organize data in a manner most likely to shed light on research problems they address.