The Centre for Investigative Journalism
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Summer Conference Events

30 June 2022

Geojournalism: How to Use Satellite Imagery to Verify Information and Uncover New Stories

This presentation takes journalists and analysts through the basics of satellite imagery, geographical data, and using imagery in storytelling to verify information and make new findings.

29 June 2022

What Can R Do for Your Investigations?

So you’ve got the fundamentals of data journalism down. You’re interrogating spreadsheets like a pro and able to use pivot tables like the data Swiss-army-knives they are. But 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.

5 July 2021

Trase.earth: Deforestation and Supply-Chain Investigations

At this free workshop, you’ll learn about the importance of covering forest-risk commodity trading, the impacts of the production of key commodities

7 July 2021

Investigating Covid Contracts

The COVID-19 response has put a spotlight on health sector spending, be it protective equipment for front-line staff, vaccines, or medicines. Globally, US $13 trillion is spent on contracts with private companies each year and spending on health is one of the largest areas – and also one of the most opaque.

7 July 2021

Aleph: the Tool that Turns Data into Leads

This free session is designed to give you an introduction to Aleph, the tool that turns data into leads.

Finding Needles in Haystacks with Fuzzy Matching

Fuzzy matching is a process for linking up names that are similar, but not quite the same. It has become an increasingly important part of data-led investigations as a way to identify connections between public figures, key people, and companies that are relevant to a story.

5 July 2019

Graph Databases

In data journalism, we tend to use relational databases – data in table form – such as Excel or SQL to do our analysis and find stories. Graph databases are different, but are incredibly useful to find connections or patterns within our data that would be difficult, if not impossible, to spot using a relational database.

Data Wrangling with Pandas 2

Your data is squeaky clean and ready to go – time to dig deep and start hunting for those elusive leads. Pandas allows you to quickly and easily perform statistical analysis on your data helping you to mine for stories and look for outliers.

Data Cleaning with Pandas 1

Data cleaning can feel more like data penance, but Pandas can ease your pain, allowing you to clean and structure your data with minimal hassle. Jupyter Notebook’s interactive environment helps you keep track of your changes and allows you to explore your data.