14/12/2016

Getting with The Times: Lessons from the paper’s Data Journalism Editor

 

Over the past few years, we have witnessed a rising adoption of data and data analytics for investigative reporting and storytelling. Despite the growing interest in data driven journalism in newsrooms, and its emergence as an academic discipline in its own right, there is a lack of systematic research into this domain, resulting in a divide between academic and industry practices.

We believe it is time for an assessment of this emerging field: How have various newsrooms across the world have adopted data in their day-to-day workflow? What are the best practices for producing high quality data driven investigative work? What are the dos and don’ts? How should we teach journalism to professional journalists, and to students?

To address this gap, we are conducting a series of interviews with industry experts in order to learn about current practices in data driven journalism and the discipline’s future directions.

These interviews are part of a larger project on the state of data driven journalism, carried out by Bahareh Heravi from the School of Information and Communication Studies at University College Dublin, and Mirko Lorenz, an information architect and co-founder of Datawrapper. These expert interviews are complemented by a survey on the state of Data Journalism globally.

Here, we have our first interview with Megan Lucero, Data Journalism Editor at The Times and The Sunday Times, and soon to be Director of the Bureau of Investigative Journalism's Local Data Lab. 

Bahareh: Hello my name is Bahareh Heravi. Here we are having Megan Lucero. Thank you very much for joining us for the interview. I am going to let Megan to introduce herself and we will then start with the interview questions. Megan thank for joining us today, and please could you give us a brief introduction to yourself and your role.

Megan: Thanks for having me. I am Megan Lucero. I am the Data Journalism Editor of The Times and The Sunday Times here in London. I have been in this data team for about three years. I originally started at The Times as an intern five years ago, but became part of the first data journalism team three years ago when we started this digital team that works across both The Times and The Sunday Times, and that role as the data journalism I started in has been evolved to me running the data team as the Data Editor. I am outgoing and will be heading to the Bureau of Investigative Journalism as the director of the new data lab in the new year.

How do you describe your role in the organisation you work in?

As the data journalism editor for the data team here [The Times and The Sunday Times], I would like to describe our data team first. The data team in The Times and The Sunday Times is a Computational investigative team. You probably ….. where you go… from journalist to journalist, from paper to paper, from whoever you are speaking to. But here at The Times and The Sunday Times it is about computational investigative journalism. So what we do is we have a statistician and programmer journalists all working together, and we work to find stories in data that you couldn’t do without computing. So my role in that as the editor is lots of things. It is coming up with story ideas, coming up with investigation of those, it is working with the team to lift up findings and lift up data of things we want to run in. It is coordinating different kinds of skillsets and different kinds of timescales and roles and getting the stories pitched to the newsdesk, and getting the content edited and things going through to get to the paper.

How would you describe “data driven journalism” to someone who has never heard the term?

Well, I think the best to describe data driven journalism is to think of it like any other way of describing journalism. I am of the belief that data journalism is a repetitive term that data journalism is simply journalism. So when you have data that drives your journalism, as a tool for journalism, it is very similar to saying pen driven journalism or typewriter driven journalism, or computer driven journalism. It is something that aids in the process of your journalism. So  data driven journalism being the kind of what aids and what the tool is there is about looking at digitisation, and looking at data and the digital sphere as your pool to swim in, as your source of data, as a means to finding stories. So finding ways to navigate it, to mine it, to analyse it, in ways to find stories and drive your journalism. That’s what my team does and that’s I think probably the best way to describe that.

What do you think/hope/believe are the main benefits/added values of data driven journalism?

For me it is not about thinking, or hoping; I know that data driven journalism is on the rise. I believe it is the future of journalism. And that there is benefits and the reason for that being that it is the source of stories. With organisations releasing records, with them digitising, and producing data every single day, on our phones, on our computers, we tap in and out of the tube, we walk down the road and CCTV captures us. Every minute of our lives data is being captured, and that’s a lot of data, a lot of information; and there are stories after stories after stories buried in that. So the benefits of being able to mine it and to analyse it is an added benefit because that is where stories are, and that’s where we need to get to.

And I actually like to speak of it the way that newsrooms think about it at the moment is you send your journalists where the stories are. So when the war in Iraq started people sent reporters to Iraq, so they had war correspondent - they sent them into war. When you have a court hearing and you send the journalist into the court because there is a story there, you know there is a story there. Similarly we send our journalist into the pool of data. We know that there are stories waiting there, we know that that’s where bodies and government bodies and organisations are producing it. We need to be able to send them [journalists] there, and we need to skill them up and provide them with people to collaborate with in order to dig in that data properly.

What is the most important aspect of data driven journalism in your opinion?

It is a few things. I think at this moment in journalist, at the end of 2016, speaking at that place I think the most important thing is the collaboration between traditional investigative reporting, traditional newsrooms, and technology and new technology advancements. I think that the most important thing is learning to bridge that. My fear is that we are going to enter into a world in which we are skilling up programmers to become journalists. But they are not skilled with how to find the story, how to find the really good lead, and lose the journalism element of it. My other fear is that we let the really great investigative journalisms die out and fall away and those techniques fall away, the intuition and the ability to listen, ability to hear, to talk to sources and know when those fluctuations happen. I think it is really important at this stage that those always remain bridged, and that the future of it is a bridge between those two; or else I believe we are going to have issues on both sides of technology advancements and traditional journalism.

What is your opinion about the relevance of data, statistics, visualisations, and coding in newsrooms?

A lot of things in there.

I think that they are all relevant, but they are relevant in completely different ways. So, data is a very wide term. Obviously I just spoke about what I believe is the importance of data as a source, as a means to find stories, as the space in which we have to navigate to find them. Statistics, I think, is increasingly important as we handle more numerical or tabulated, or list forms of information, needing to make sure that we do not jump to spurious conclusions, I think having a good understanding of statistics is very important. I would always recommend Stats 101. Every journalist should be able to do that anyways.

Visualisation I have always believed is an added effect. I think visualisation should visualise in a technological way only when it pushes you to see something that you couldn't see in a static way. I am very much against visualisations that move just to move. I think visualisation has to play a very specific role. You have to think of is as a new medium. Sometimes the best way to tell a story is on camera, sometimes the best way to tell a story is in written word, sometimes it is in a visualisation. But I think sometimes people just assume you can tack a visualisation onto any kind of story... sometimes it is TV, sometimes it is radio, sometimes it is written. But visualisation is the next one I think, we have to think of when is something best visualised, and how we visualise that.

Coding in newsrooms is a completely different element. I think it is important for all journalists to just have a basic understanding of HTML and coding. Mainly because the computers and the laptops they are using are based on it. It is good to have an understanding to know how to get that information off of it in case you do need it.  It is more important to me that journalists know what is possible, not necessarily how to do it. But I do think it is important to have programmers and journalists working together. But I wouldn’t say you need to have an entire newsroom of journalists [programmers]. I think having some people that are very skilled in programming is going to be important to aid a lot of journalists, but I think what’s even more key is for journalists to know what is possible.

If you would be the editor-in-chief, what would be your first action to have more data driven news reporting?

That’s a tough question!

I think there needs to be an element that comes from the top from a lot of news organisations. They need to understand that as journalists they are expected to stay on their beat. But that a normal expectation for any newsroom that you have to know your beat well. Nowadays you need to know when the latest data release for your beat is dropping. If you are a crime you need to know when the official statistics drop, you need to know how to collect local crime reportings, how you can get that data really quickly. I think that would be one of the first things that I would say is that knowing your beat means you need to know the datasets, and you need to know when they are happening, and in order to know that I would want to equip my newsroom with the means to do that. The problem is, as I mentioned, the bridging between traditional and old school journalism, and the newer form could be quite intimidating and could be quite awkward if you force it. So I think a pilot program would be a good thing to start things off with. Get a handful of journalists who are more open to that idea, getting them paired up with a data journalist, or a programmer, looking through the datasets of their beat, writing scrapers to monitor sites relevant to their beat, writing bots to notify them when things are updated, building a dataset of historical databases relevant to their newsbeat, working with them as they report throughout several weeks or months, to see how you can aid the process. Find ways in which if a journalist is doing something over and over again, and write code to do that instead of manual work happening over and over again. Looking at doing an audit of the journalistic process to see how that can be aided, and being very clear that it’s about aiding the journalists and aiding the newsroom in getting stories. I think it would be important to say, in short, that knowing the data on your beat is expected of you, but I then want to go a step further and [say that] you need to actually be able to back that up with support, and like I said whether that’s through a pilot program, or whether that’s having digital team get paired up with journalists to execute that.

How should we teach data driven journalism to others - younger and older, less experienced and more experienced?

I actually think that you don’t need a different technique for different types of journalists. It kind of goes back to what I just said, what you want to do is that you want to be able to prove to the journalists that technology and computing can make their jobs easier, can make them better journalists, can get them stories no one else can get them, that can aid their work, that can save them time. Whether you are an experienced journalist or an expert journalist, [with] really good understanding of digital and data, [or not], those are the key principles in selling it or selling anything to a journalist who doesn’t have very much time to begin with, whose editors are drilling them, and saying that they’ve gotta get a lot of things done, x many stories out by the end of the day. Increasingly journalists do not have time. Whether you are a young, experienced or not. So I think that application comes to it. But then again what is important to each journalists, what they need to get the job done, what would help them is going to be completely different person to person. But I think the fundamental principle about approaching them saying what is something you do over and over and over again, listening to that, helping write a script that does that for them. Here is this dataset that now the editor has told you that you are expected you know about, what are your fears, what is it that you understand or don’t understand, how could we make this easier, and then helping them understand how all of these things, computational methods, scrapers, bots, analysis, statistics, all these things help you get stories that you never would have before. I think every journalist would be open to that. I just, like I said, the application to each person then on that principles is different.

Being involved with this area of work/expertise: Is there an observation you made in the last few years that was a surprise to you? For example, were there any unexpected areas of application or unexpected barriers to adoption?

I’d say, all of those things.

So I have been doing this for several years, as you know. There is a couple of things. I think you are missing one more question at the end of that. Of course there are unexpected areas of application. There is journalist who, when I started told me that Twitter is a joke and that no one would ever use it, and now is like the biggest tweeter, and uses it for every sort of possible thing, from getting sources, to getting quotes, to tweeting stories, writing stories about social media. So, I watched that evolution of a very old school journalist, go from the biggest sceptic, to kind of the the biggest user of it. And similarly that same journalist kind of moving into the datasphere, watching something transform in front of their eyes, getting a story they know they could have never gotten without it. Getting it at quicker rate that you ever could have expected. So I guess I am constantly surprised by people who might have been sceptics.

On your second question about barriers to adoption, I had this naive belief that, again, if you apply the concept I just told you, if you apply the concept saying that I am just trying to make your life easier, I am just trying to help you get the stories you would never get before, and get them quicker than anyone else, and get the ones that no one else would get, you’d think that would be a normal application. You would think every journalist would be jumping up and down, wanting to be trained, wanting to be paired with data journalists. To me that seems simple, to me being a great journalist is being able to be resourceful. You gotta get your best contacts, you gotta make sure you know everyone in the industry, you gotta be the kind of go to. And part of that you would think, one of your best contact would be your data. So I was quite surprised when actually it wasn’t as big of an uptake for a lot of people.

But like I said, I think all these things take time. We are working in an industry of change. That’s what really this is. Yes, I am working in data journalism, but ultimately I am in the industry of industry change. It’s about changing the industry of journalism. And changing any kind of industry is very difficult. People are obviously very fearful of what this all means, and what their jobs are, and the fear of automation of their work, and all that kind of stuff.
So there is a lot to learn about human experience, and about human fear for change and technology, and the surprise in which people kind of jump out or not.

I think last thing I have learnt is actually that the UK has a long way to go in terms of actually making data possible. So it has been a lot of advances and opening data up, or fighting for FOI to be maintained. But the ultimate thing about it is that a lot of this data should be public. When you look at the US we are still very far behind in terms of open data, in terms of how data is published. It is very clear the more stories I work on and the more datasets I look at, that the government bodies that are producing this data, very clearly have not made it systematic. The data is so messy that there is no way they could be analysing it in order to inform policy. And that as a journalist we are kind of doing the work for them.

And I find it interesting not just from the story perspective, but as a citizen, as a person who lives in a globalised state, we need this. So the work that I do about using technology to advance journalism needs to happen at every element of our society. It has to happen -- this kind of technology advanced they need to happen in the government, they need to happen in the public sector, private sector -- it needs to happen everywhere, for journalism to improve as well. You see the change in Obama’s policy in the U.S., saying Chief Technology Officer and Chief Information Officer, requiring that every government body has to make machine readable formats. That’s what led to a lot of very interesting open data projects, a lot of cool stuff you see out of the New York Times, Washington Post, and all over the place [in the U.S.], has a lot to do with the fact that the U.S. have to release their data in an open and constant and comparable format. So I think I am very surprised to see actually the long way we have to go in order to make it happen here.

If you have enjoyed this interview please take part in the Global Data Journalism Survey, and let us know about your experience in this area.

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