  Many software engineering research papers rely on time-based data (e.g.,
commit timestamps, issue report creation/update/close dates, release dates).
Like most real-world data however, time-based data is often dirty. To date,
there are no studies that quantify how frequently such data is used by the
software engineering research community, or investigate sources of and quantify
how often such data is dirty. Depending on the research task and method used,
including such dirty data could affect the research results. This paper
presents the first survey of papers that utilize time-based data, published in
the Mining Software Repositories (MSR) conference series. Out of the 690
technical track and data papers published in MSR 2004--2020, we saw at least
35% of papers utilized time-based data. We then used the Boa and Software
Heritage infrastructures to help identify and quantify several sources of dirty
commit timestamp data. Finally we provide guidelines/best practices for
researchers utilizing time-based data from Git repositories.
