Three years ago, we thought that Data Science Quarterly would be journal at the intersection of data science and journalism. As we stated in the initial plan: To trust the news, we want to see the data behind it. Show us the research. Show us the science. To trust an argument, we want to see evidentiary support and correct logic. These values are reflected in the journal’s tagline: “Following the data, leading with science.”

We remain committed to the ideals of the initial plan. We welcome submissions at the intersection of data science and journalism, and we are keeping the journal’s tagline. But we now envision a journal with a broader mission to promote data science as a discipline.

We will be publishing articles relevant to all organizations, as well as to social and political discourse. We are especially interested in publishing research articles and teaching case studies for data science education.

Consistent with its educational mission, Data Science Quarterly will also be hosting a collection of public, multilingual repositories on GitHub. These repositories will concern case studies and applications with rich data sets and analyses in R, Python, Go, and other languages.

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