R packages offer the chance to distribute large datasets while also providing functions for exploring and working with that data. However, data packages often exceed the suggested size of CRAN packages, which is a challenge for package maintainers who would like to share their code through this central and popular repository. In this talk, we outline an approach in which the maintainer creates a smaller code package with the code to interact with the data, which can be submitted to CRAN, and a separate data package, which can be hosted by the package maintainer through a personal repository. Although repositories are not mainstream, and so cannot be listed with an “Includes” or “Depends” dependency for a package submitted to CRAN, we suggest a way of including the data package as a suggested package and incorporating conditional code in the executable code within vignettes, examples, and tests, as well as conditioning functions in the code package to check for the availability of the data package. We illustrate this approach for a pair of packages , and , that allows users to explore exposure to hurricanes and tropical storms in the United States. This approach may prove useful for a number of R package maintainers, especially with the growing trend to the sharing and use of open data in many of the fields in which R is popular.