Journals, research funders and research groups such as Innovations for Poverty Action are increasingly recognizing the value of research transparency. Research transparency includes pre-registering studies and sharing materials such as data and code to allow others to re-analyze the reported results.

Proper data and code management during a project are essential for transparency after a project’s completion. They are also important for internal use, as projects often run for multiple years, with several staff members working on them sequentially.

This guide outlines best practices in data and code management. The scope of the guide is to cover the principles of organizing and documenting materials at all steps of the project lifecycle with the goal of making research reproducible. The guide does not cover best practices in designing surveys, cleaning data or conducting data analysis. In each section, we explain the “what,” “why” and “how” of each recommended practice.