Abstract
Abstract Data harmonization is an important method for generating the requisite datasets to support big data analyses. To date however, articles about data harmonization are field-specific and highly technical, making it difficult for researchers to derive general principles for how to engage in and contextualize data harmonization efforts. This article provides general guidance and criteria for researchers who are considering undertaking such efforts or seek to evaluate the quality of existing ones. We derive these guidelines from the extant literature and our own experience in harmonizing data for the emergent and important new field of COVID-19 public health and safety measures (PHSM). We further introduce the methodology we employed for engaging in this data harmonization as a blueprint for researchers interested in engaging in manual data harmonization.