From novice to expert: Supporting all levels of computational expertise in reproducible research methods

Training and documentation for on-premises infrastructure represent the foundation of most institutional support for computational researchers. For most academic research institutions, however, these approaches fall short of meeting the needs of diverse researchers with different levels of experience with data-intensive research. We describe a framework for characterizing levels of computational expertise and relate this model to informational support provided for biomedical researchers at a non-profit/academic research center. Our model differentiates between novice, competent practitioner, and expert users of reproducible computational methods, and is related to the composition and needs of an entire research community. We specify methods best suited for researchers with different levels of expertise, including formally structured short courses, code examples/templates, and online wiki-style documentation. We provide recommendations to encourage the development and deployment of these resources, and suggest methods for assessing their effectiveness. Supporting multiple types of informational resources for researchers with different computational needs can be labor-intensive, but ideally increases computational ability for the entire institution.