Moving Towards FAIR Data Practices in Pharmacy Education

Abstract

Pharmacy schools are generating significant amounts of data across the training continuum, including data about student selection, performance, and job placement. However, current data practices limit our ability to effectively leverage the vast amounts of data available within and across our institutions. In an effort to improve data practices and promote the quality and reusability of data, the FAIR guiding principles for data management and stewardship were developed and published in 2016. These principles state that digital objects should be [F]indable (e.g., data have a unique identifier and are registered in a searchable resource), [A]ccessible (e.g., data are retrievable by their identifier using an open, free, standardized protocol), [I]nteroperable (e.g., data use a formal, accessible, shared, and broadly applicable language and include qualified references to other data), and [R]eusable (e.g., data are described with accurate and relevant attributes, released with a data usage license, and meet domain-relevant community standards). This commentary advocates for improved data practices and provides recommendations for advancing FAIR data principles in pharmacy education.