The second edition of Getting Started with Data Journalism has just launched and over the next few weeks I’m going to be bringing you some beginners’ guides to data journalism based on the book, so you can get a taste of what’s in there (a lot of tip, techniques and info), as well as potentially get started as a data journalism novice.

A lot has changed in data journalism since the first edition of this book was published in August 2013. Tools for cleaning, analysing and visualising have come and gone (Google Fusion Tables, gone too soon!), new trends in storytelling have emerged, new projects based on data journalism have been launched.

But many of the fundamentals of working with data remain the same – particularly in terms of telling stories, even while the Covid-19 pandemic has put data journalism front and centre in much of the news coverage, with tables, graphs and charts now a common sight.

Want more? Buy Getting Started with Data Journalism, a beginners and beyond guide to finding, cleaning analysing and visualising data in any size newsroom.

Why Data Journalism

“Anyone can produce stories from data, equipped with basic mathematics*”

Rohit Saran, India Today group

*plus some spreadsheet formulas and some free tools

What makes data journalism skills worth learning? Because they can help you find stories, or add weight to ideas, from data that is becoming more freely available and plentiful. Because you can do things quicker and easier, like analyse your FOI responses in a flash. Because visualisations can help tell stories in a more interesting way. Because if you don’t other people will beat you to these stories.

The key to getting to grips with data journalism is remembering that it is just like all other types of journalism – what is the story?

All the skills you would use to find a story in any other situation still apply when you are looking at a spreadsheet full of numbers.

^{Some headlines from data journalism related stories (any excuse to get a Star Wars reference in)}

In many ways, you set about questioning a dataset or putting together a Freedom of Information request in much the same way you would think about interviewing a contact. You work out what information you are hoping to get back and the questions you might need to ask to do that.

Things that might make a data story:

• Big, bigger, biggest (or small, smaller, smallest)
• Fastest growing, stalling or being left behind
• Common and rare
• Hotspots and how we compare
• Correlations and connections
• Why?
• Fact checks and explainers

People want information about things that affect their lives – how a government policy will impact them, how well local services are performing, how where they live compares to other places and whether things are better or whether they need to change.

Many stories have scope for data journalism. Many stories already are data journalism.

If you have ever written a story on crime figures, life expectancy, GCSE results or the number of people out of work, you are already doing data journalism – mainly because data journalism is a buzzwordy title for the kind of reporting journalists have been doing
forever (or in some cases avoiding doing forever).

The following example shows how combining traditional journalism skills with data journalism skills can help to build the story.

Mental health

Data skills

Monthly NHS figures for referrals show the number been sent for mental health help has increased over the course of the pandemic and is now higher than in 2019.

Traditional skills

Are doctors’ groups, such as the Royal College of Psychiatrists, seeing this increase in referrals, and, if so, what do they think is behind the rise. What do they think could help support people who need mental health support? Can you ask the NHS what it is doing to help those being referred, and what resources it has in place to deal with a rise?

Data skills

Are there other datasets you can look at to expand the story – are there figures looking at the number of people referred as an emergency. Is this an issue that also affects children? What do figures for antidepressant prescriptions show? Are some areas harder hit than others? Are people being sent further from home to access inpatient care?

Traditional skills

Can you find people who have been affected by this? It could be people who have been able to get the care they needed after being referred. It may be those who have been referred but are worried about long waits. It may be people, or families, unhappy with the care they are getting.

Go where the stories are

Another reason to explore learning to do data journalism is data journalism can be the answer to the story drought.

Newspapers and online come with a high demand for new content, and ideas are sometimes in short supply and sources aren’t always supplying you with good tips and press releases are of varying quality but at least with data a bit of digging can lead to something new.

Working on the Reach Data Unit, our main day to day job is to analyse available datasets (a mix of the ONS releases for the day, ideas for things we think might have datasets and any datasets or FOIs we’ve got hanging around) and come up with possible lines for the papers in the group – covering the two data journalism steps above (and sometime a few of the traditional ones as well), while journalists on the regional titles, with the local knowledge and contacts, fill in the rest of the traditional journalism steps.

Doing this, we can often come up with four or five potential leads a day, just working through datasets, often looking for the basic story ideas (see above) or doing (often fairly simple) analysis (combining datasets, finding rates and percentages). The emphasis is mostly on finding the most interesting things we can from the dataset as quickly as possible, because the story idea needs to be reporters early so they can start getting comments on it.

There are interesting stories out there, so getting the skills to go get them is definitely worthwhile.

What you need to get started?

In order to get started with data journalism, there are a few tools you need, many of which you will already have, and all of which have free options.

• A programme that opens spreadsheet files, such as:
  • Microsoft Excel
  • OpenOffice Calc or LibreOffice – both of which are open-source software, so are free to download and use.
  • Alternatively, you could use Google Sheets.
• Depending on what files you are working with, you may also need a PDF reader and a programme to open word documents – there are versions included in both LibreOffice and OpenOffice, or again you could use Google Drive.
• A dataset or several datasets – the next section looks at where you can find data.
• A place to write stories and a means of publishing them

As well as these, the following may be useful:

• A Google account – this gives you access to online spreadsheets and visualisation and mapping tools, and it is helpful for storing and sharing documents.
• Something to visualise data with – there are several different online options, for example:
  • Google Charts
  • Datawrapper
  • Flourish
  • Tableau, which is available as both a free and paid for version.
• Open Refine – for cleaning data
• Geographic information system software for analysing and editing spatial information – QGIS is a free open-source one

Want more? Upcoming posts will cover more on how to clean, analyse and visualise data.

Or, buy Getting Started with Data Journalism, a beginners and beyond guide to finding, cleaning analysing and visualising data in any size newsroom.