Summer Conference Events

Data journalism has been around for a very long time... but the existence of dedicated data desks in UK newsrooms is a relatively new concept. In fact when the CIJ started teaching data journalism - then called Computer Assisted Reporting - in the early 2000s, very few people were interested.

Tech companies are harvesting a terrifying amount of personal data from users all the time – and the practice is opaque by design. This talk will look at routes to discovering what data they hold. In particular, we’ll explore how to use subject access requests (SARs) combined with data analysis and other journalistic techniques to paint a picture of how tech and social media companies see and categorise us all.

Hands-on. Beginner [B]-Intermediate [I]. Sooner or later you know you’ll come up against a dataset so big it’s going to crash Excel if you even try to open it. Maybe your questions are becoming too complex for Excel’s built-in analytics tools to handle.

Hands-on. Beginner-Intermediate. This three-part hands-on express data journalism course will introduce you to the basics of data analysis in Google Sheets. Suitable for beginners (part I) and intermediates (parts II and III).

Hands-on. Beginner [B]-Intermediate [I]. See each session for the details. This three-part series introduces participants to the power of Python, by journalists, for journalists. We'll help you take your first steps on the road to code, from the very basics, to working with giant spreadsheets, to extracting structured data from the web.

Data journalism has been key to uncovering patterns for investigations for decades. The availability of open-source tools has made data journalism accessible to all newsrooms. This session will give you a bit of history about data journalism through some groundbreaking work.

How do you add a new skill as a local journalist? From two different perspectives, Helena Bengtsson and Claire Miller will talk about how they educate and inspire regional reporters to work with data journalism methods.

One of the most powerful data analysis tools is mapping. It allows you to uncover patterns you would not see in rows and columns of data. From statistical trends, such as population characteristics, to locations of events or incidents, QGIS is a great tool to reveal geographic patterns in data.

Overlaps between natural resource exploitation and exploration licenses and protected area can be a great starter for diving into an environmental investigation! But just why and how could you apply this process in a systemic manner when it comes to global extractive giants?

Hands-on. Beginner-Intermediate. Sooner or later you know you’ll come up against a dataset so big it’s going to crash Excel if you even try to open it. Maybe your questions are becoming too complex for Excel’s built-in analytics tools to handle.