In early 2017 two colleagues, Gary Younge and Damien Gayle, approached me in The Guardian newsroom. They wanted to examine knife crime in the United Kingdom. While there was no shortage of write-ups detailing the deaths of victims of knife crime, follow-ups on the pursuit of suspects, and reports on the trials and convictions of the perpetrators, no one had looked at all the homicides as a whole.

My first question was, how many children and teenagers had been killed by knives in recent years? It seemed a straightforward query but once I set out to find the data it soon became apparent—no one could tell me. The data existed, somewhere, but it wasn't in the public domain. At this stage I had two options, give up or make a data set from scratch based on what I could access, build and verify myself. I decided to build my own data set.

Why Build Your Own Data Set?

Data journalism needn't be solely based on existing data sets. In fact there is a great case for making your own data. There is a wealth of information in data that is not routinely published or in some cases not even collected.

In building your own data set you create a unique set of information, a one-off source, with which to explore your story. The data and subsequent stories are likely to be exclusive and it can give you a competitive edge to find stories other reporters simply can’t. Unique data sets can also help you identify what trends experts and policy makers haven't been able to spot.

Data is a source of information in journalism. The basis for using data in journalism is structured thinking. In order to use data to its full potential, at the outset of a project the journalist needs to think structurally: What is the story I want to be able to tell and what do I need to be able to tell it?

The key to successfully building a data set for your story is to have a structured approach to your story and query every source of data with a journalistic sense of curiosity.