Workshop Recap: Introduction to Data Journalism

We all know that data are all around us—from the apps that track our every movement, to education, criminal justice, health care and beyond. But data can be misleading, misrepresented, and even wrong. Where should you go to find data and how do you make sure it says what you think it does? In this October 19 workshop, Jonah Newman outlined where to look for data, how to bulletproof it, and how to use it effectively and responsively to tell compelling stories.

Jonah Newman is a Chicago-based data and investigative reporter. Most recently, he was the senior editor for data and investigations at Pacific Standard magazine. Before that he was a reporter at the Chicago Reporter, where he used data to tell stories about policing and criminal justice in Chicago and Cook County. He grew up in Minnesota and graduated from Northwestern University with a degree in journalism in 2012.

Why are Data Important?

We all know that data are all around us-from the apps that track our every movement, to education, criminal justice, health care and beyond. But data can be misleading, misrepresented, and even wrong. Where should you go to find data and how do you make sure it says what you think it does?

Cleaning Data

Introduction to Data Journalism October 19, 2019 Presenter: Jonah Newman We all know that data are all around us-from the apps that track our every movement, to education, criminal justice, health care and beyond. But data can be misleading, misrepresented, and even wrong.

Analyzing Data

Introduction to Data Journalism October 19, 2019 Presenter: Jonah Newman We all know that data are all around us-from the apps that track our every movement, to education, criminal justice, health care and beyond. But data can be misleading, misrepresented, and even wrong.

Pitfalls

Introduction to Data Journalism October 19, 2019 Presenter: Jonah Newman We all know that data are all around us-from the apps that track our every movement, to education, criminal justice, health care and beyond. But data can be misleading, misrepresented, and even wrong.

Resources for Acquiring Data