To promote reproducibility, WRA expects researchers to identify and cite data sets and/or code used in their experiments and studies. These may be large or complex data sets that can include, but are not limited to, data from microarray, genomic, structural, proteomic, or video imaging analyses. Authors should cite both the data set repository and the published article in which the data set and/or code was originally described. Citations of data should be included in the reference list with persistent unique identifiers (e.g., active DOIs, accession numbers, etc.). If computer code or software was created to generate results or interpret data, then a statement to that effect should be included in the “Data availability” paragraph. In cases where the software is publicly available, the URL of the software informational page should be provided. It is preferred that authors use established, publicly available data type-specific repositories. If there is no appropriate repository available, general publicly available repositories should be used (e.g., Dryad, figshare, etc.).