  In 2022, the Journal of Statistics and Data Science Education (JSDSE)
instituted augmented requirements for authors to post deidentified data and
code underlying their papers. These changes were prompted by an increased focus
on reproducibility and open science (NASEM 2019). A recent review of data
availability practices noted that "such policies help increase the
reproducibility of the published literature, as well as make a larger body of
data available for reuse and re-analysis" (PLOS ONE, 2024). JSDSE values
accessibility as it endeavors to share knowledge that can improve educational
approaches to teaching statistics and data science. Because institution,
environment, and students differ across readers of the journal, it is
especially important to facilitate the transfer of a journal article's findings
to new contexts. This process may require digging into more of the details,
including the deidentified data and code. Our goal is to provide our readers
and authors with a review of why the requirements for code and data sharing
were instituted, summarize ongoing trends and developments in open science,
discuss options for data and code sharing, and share advice for authors.
