I’ve come specifically to the Open Knowledge Conference for the track on data journalism (although I’m very interested in the open data scene anyway). It was a call to action more than an educational exposition. Data journalism doesn’t have a set path nor definition which is why there’s a lot of journalism falling under the term ‘data journalism’ that are, underneath it all, very different species. Just as mathematics is composed of a ranges of disciplines yet most people encounter it as one overarching topic.
I’m having an amazing time in Berlin and I’m sure I’ve consumed more than I can digest in terms of data. But here are some points I noted from the speakers Simon Rogers, Stefan Candea, Caelainn Barr, Liliana Bounegru and Mirko Lorenz, which I’ve added my thoughts to here:
1. “There needs to be defined long-term goals for data journalism training as the field has widened” – I believe that the different disciplines are becoming evident as tools with wider uses are being tinkered with (I wouldn’t go so far as to say adopted), more so than the field has widened. I do not believe in long term goals either. To evolve into a specialist species one has to adapt to ones environment. Now the data environment is changing at a web rate which is far too fast for long term goals.
2. “It’s about stories AND words – it’s just another source” - Old school journalism used to rely on a network of sources. Data journalism relies on a network of resources. So all journalism today should rely on a network of sources and resources working in tandem, working together, in sync. Old school journalism applies today just as it always did. You need to be able to read and rely on the validity of your sources. You need to understand their agenda and their limitations. In the same way you need to be able to do all these things with data and the resources you are working with.
3. “Data for journalists is a great resource but not the golden bullet” – I agree. The golden bullet is the journalistic mindset. The ability to spot something that isn’t right, that shouldn’t be. This is one characteristic but with data journalism you’re using the other side of the brain. The ‘training’ that is needed is to learn to use your other numerical side as a resource also. If you don’t have a well tuned journalistic mindset you won’t be a good data journalist and I fear this mindset is being left at the door when journalists approach data (especially when being trained) because using the left hemisphere of their brain is so alien to them they feel they’re in a completely different microcosm.