Data Science Quarterly promotes data science as a discipline, showing its relevance to social and political discourse. Data Science Quarterly combines the best attributes of academic journals and popular news magazines. Its articles draw on high-quality empirical research written in clear, concise language that anyone can understand.

What is data science? We see data science as an emerging, eclectic discipline that draws from several other academic traditions. Data science relies on mathematics, statistics, and computer science. It is a practical, applied science, more in tune with engineering than physics, more in the style of business than economics. Most recently, driven by the pace of technology, data science has become identified with machine learning and artificial intelligence (AI).

What is the role of data science? How people come to data science matters less than where they take it. Data scientists can play an important role in ensuring well-informed public policy by insisting on data integrity, data and research methods transparency, and data privacy to protect individual rights. {\em Data Science Quarterly} publishes articles that are socially and politically relevant. {\em Data Science Quarterly} is nonpartisan.

Trust in data and science. Data science takes on added significance in the throes of a pandemic, amidst ethnic, social, and political divides. Data science affirms faith in the scientific method, providing real, meaningful solutions to challenging problems. We value rational decision-making guided by science, reliable and valid measures, relevant data, and trustworthy models.

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.

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