There are three tiers of journalism in the UK at the moment – national, regional and hyperlocal – but in all the discussion and excitement over open data, the voices of journalists working at the coal-face in the middle tier tend to be absent. That’s a shame, because regional news offers some fascinating and unique challenges for data journalism and computer assisted reporting.
At one end of the scale there’s national journalism, which covers big issues affecting all regions of the country or stories of national interest. In most media national journalism tends to be biased towards the south in general and London in particular, and in newspaper terms there’s a partisan/issues bias too, along with a clear character.
Then at the other end of the scale there’s hyperlocal journalism, geared around my street, my postcode, my community. These are organisations tackling incredibly specific situations, interested in minutiae and detail, as well as the impact of wider stories on the communities in question. It’s all about applying the national news to a very specific set of circumstances.
Somewhere in between, on a sliding scale depending on the size of the news organisation, is regional journalism. At the moment that’s where I fit in – at the city- and county-wide level depending on which paper I’m writing for. The stories I follow up are a mix of both – national stories with an impact on the communities I write for, and street-level stories with wider implications. We also cover wide regional stories with an impact on a substantial proportion of our readers – council stories, crime cases, the sorts of stories which nationals would not cover at all while hyperlocals would cover only the relevant parts.
After a conversation with the BBC’s Martin Rosenbaum at Hacks and Hackers, I started to understand that regional journalism has a particular set of needs and problems when it comes to data journalism. National news needs big picture data from which it can draw big trends. Government ata that groups England into its nine official regions works fine for broad sweeps; data that breaks down by city or county works well too. Hyperlocal news needs small details – court lists, crime reports, enormous amounts of council information – and it’s possible to not only extract but report and contextualise the details.
Regional news needs both, but in different ways. It needs those stories that the nationals wouldn’t cover and the hyperlocals would cover only part of. Data about the East of England is too vague for a paper that focuses primarily on 1/6 of the counties in the region; information from Breckland District Council is not universal enough when there are at least 13 other county and district councils in the paper’s patch. Government statistics by region need paragraphs attached looking at the vagaries of the statistics and how Cambridge skews everything a certain way. District council data has to be broadened out. Everything needs context.
The great thing about that? There are unending opportunities for good data journalism in regional news – opportunities to combine new technology and open data to produce something that’s relevant and useful to as many individuals as possible. The question is how we exploit them. I believe that we start by freeing up interested journalists to do data work beyond simply plotting their stories on a map, taking on stories that impact people on a regional level.
How do school catchment areas affect house prices? Since the county council decided to turn the lights off at midnight on certain streets, has there been an increase in crime? How have mental health service closures hit NHS waiting lists in the region? We should be using open data and freely available tools to do good regional journalism and helping people to find out.