Openly shared data and analyses are essential for rapid progress in ecology and other areas of science. Because computer software is an intrinsic and inextricable part of modern analytical methods, making data publicly accessible is only the first step in full transparency. Making open-source code for analyses and models is the second step, but given the pace of software evolution and development, reproducibility of analyses is often precluded by lack of documentation and "code-rot" (old code that will not run on current versions of software). Data provenance tools provide automatic collection of information that can improve analysis and reproducibility. In this workshop, attendees will: 1) learn about the topic of data provenance; 2) get experience using tools for collecting provenance; and 3) use these tools to debug code and improve scientific workflows.