This site compiles data journalism resources so that they would be easily available to students, journalists, and the instructors who teach them. It includes manuals, textbooks, teaching videos, tutorials, and sample syllabi. Many of these resources were produced by instructors and centers at the Columbia University Graduate School of Journalism. Others are tools and platforms that allow users to clean, scrape, analyze, and visualize data. We also included useful resources produced by news organizations and training centers.
We define data journalism broadly to mean the use of data in order to find and tell stories in the public interest. This may involve cleaning and analyzing data and conveying that analysis in written form. It can mean visualizing data or building news apps that help readers explore the data themselves. The field also encompasses the use of computation—algorithms, machine learning, and natural language processing—to effectively mine both structured and unstructured information to find and tell stories. Whatever the case, the ability to use, understand, and interrogate data can be applied to nearly every area of journalistic practice.
This site was made possible by a grant from the John S. and James L. Knight Foundation.
