Investigative data journalism in the public interest - Data journalism (part 2)

Investigative data journalism in the public interest – Data journalism (part 2)

yeah my name is Charles I work as the data lead for the Bureau of Investigative Journalism and more specifically the bureau local team the bureau local team does collaborative investigative data journalism projects where we investigate and once we have a story we collaborate with local journalists around the country to tell that story better before we go into that I changed oh this wonderful before we go into that I'm just gonna go quickly into algebra local came to be and why bureau local came to be or at least how I feel about it the how is quite simple when the bureau of investigative journalism was created around eight years ago the goal was to feel a perceived gap in investigative reporting journalism was undergoing and still is undergoing a crisis in terms of funding models and investigative team were getting cut because they require quite a bit of resources in time and that's why the bureau was launched now a few years ago the bureau did an independent audit of its work will ask for an independent audit to be done and what came back was yeah you're doing that well but the organization you're collaborating with and who you're because when the bureau has a story it finds the best partner for that story and then at the end it gives the story for free usually to that partner so if it's political story maybe it's give it to The Times if it's more of a social issue maybe the Guardian if it's drawn attack in the Middle East maybe it's with the Washington Post it all depends but those organization all still had strong investigative journalism units the people we were not collaborating with were local media we're investigative journalism had been caught even more than elsewhere so it became apparent that the bureau needed to step into that that place and that's why Bureau local was created and data journalism became obviously a great way to do that because you can scale data and have both the national story and the local story and collaborate with local journalists which was the only way that the bureau was going to be able to do it because we're this organization and we cannot have journalism or a home journalists everywhere this is a map I love it's the 2015 general election and if you take all the people who didn't vote and all the constituencies that party would have won the majority so obviously the system kind of doesn't work if that's the result of the election and when I look at it from someone who's in the media the way I see this map is that I see a disenfranchisement that can be quite easy to see when you look at the national media that's providing averages and I don't know the economy might well go up for a certain quarter but someone in Sunderland will say no it's not going up for me and someone groans would be will say no it's not going up for me and it don't feel like they are connected to the narrative meanwhile when I used to work with Clara Trinity Mirror we did lots of local reporting and data journalism that was meaningful to the people and when I was reading the article we were publishing it became quite obvious in the comment that people know what's happening in their local authorities but they don't feel like they're being represented in the other mainstream narrative that provide averages more than anything else to them and for me data journalism as the potential to both connect those two things together and say it's not something that's happening only on Sunderland but in fact in a turd of local authorities in the UK this is what's happening and then you're not communicating an average you're communicating the local the local realities and putting them together so how does the Bureau local kind of see data journalism well to basically repeat the stevedoring code it's just journalism and I'm wondering now you can place bets as if the four of us are gonna say that line and I think you have really good odds from having been to a few data journalism conference and in fact when we kind of communicate especially to collaborate with local reporters around the country we're starting to drop the word data because it kind of scared some of them away instead of exciting them like a geek like me might be so instead of data I'm starting to use more some like digitized information well if you say data journalism is information journalism it you kind of see why it's actually just journalism we all know here that data is not number it can be a boolean you can easily turn a string into data and more importantly for us data is social in that it is the account of communities it's the people who create data public bodies reporting on their staff their expenses there's always a human component behind the data and it's always what we want to go to the bureau local and the bureau of investigative journalism don't want to report on the numbers it's really much about being able to put the finger on what is the local reality as I was referring to with the map before you always want to be able to tell the story with the numbers and with the local story if you're just giving numbers it's a bit it's not really engaging and it can be dismissed as anecdotal that's just one incident that something has happened sorry no if you give this is the number is not gonna be really engaging and if you tell just the human story it's gonna seem like it's just anecdotal but putting the two together you usually end up with very strong pieces of journalism which is what we always want to go to so data is not deleted once we have the number we still need to find the story and see if what the numbers show really ends up being true my motto and a big part of your local is about making the available accessible so this type of journalism is more and more important because the public bodies are producing more and more data and more and more open data and more than journalists can make sense of and if you're not able to interrogate that data well then society is becoming more opac and the thing is there's a lot of resources that are missing in journals and took it at the moment in terms well not just in terms of skills but also in terms of time but if you go in terms of skills and you want to investigate prescription data in the UK well the file is published monthly but it's about elephant million rows so that's 10 million rows more than Excel can endow so if that's the only tool that you have to look at data as a local journalist you're done there's no investigation to be done you're not able to look into it so that's our role as an organization to help make what's available accessible in term of time well this is an example if you wanted to look at drug crimes in your area well those files are published monthly for each police forces so if you want to look for a year in your area that's 12 files if you want to be able to compare it with every other local police forces that's 45 police forces so times 12 540 files that you need to all open to filter and to copy/paste in one master file if that's all the technique you have when it can be done in seven lines of Python or R and then processed in 22 seconds so when I talk about data journalism for me it's simply about using technology to access the information that would that we would otherwise not be able to surface for local journalists during the process of opening all the file that's not necessarily possible because now we're talking to journalists who have constraint in their contracts in terms of stories they need to publish it each week a number of clicks they're not going to get so if you're not guaranteed that you're gonna get a story out of it it might not be worth it because if you don't reach your quotas and someone needs to be fired well you're in contractual breach at the end of the week so there is a real need for making that available accessible and to me beyond that it's the only way to turn transparency into accountability there's a big open data community in the UK and I think the open data community the statistics community the journalism community really need to all join forces together to be able to tell those stories and to have all the resources we have become effective by Olding power to account it needs to be done I'm gonna go to a bit of like some stories we did that I think are interesting for a statistic society not long after we launched terrorism a like we launched in March and obviously in April terrorism a announced the election for June so while we were thinking are we're gonna take time that love this network traveled the country me the journal is build links we were forced into stories right away I think an interesting one we did is we partners with two statistician to get the best demographic breakdown and voters data we could for the UK and then we invited people around the country to a hack day that happened simultaneously in five cities to look into the data together the top left corner of that picture is Cardiff the top right is London the bottom right is born with the bottom left is Birmingham and the middle one is Glasgow and together we look for stories and something done okay I'm gonna make a small parents's something that I see increasingly happening because we have too much data available is that we start sometimes actually using too much of it and there's people who just love Turing data in machine learning and they don't investigate the data they expect the Machine and the model to tell them the answer when we say that we're not looking at numbers we're looking at something social at the account of communities it's about finding what the number really mean and having the investigative question so what became most interesting from that voters data was taking into account the fact that because it was a snap election and because you keep wanted to support the conservative a lot of UK voters were left orphaned they didn't no longer had a UK person to vote to same thing for the Greens an observable ously same thing with the new voters which is what we modelled with the statistician as well the new voter for each constituency and taking all of that into account if we summed each of these votes up and especially just the UK pawns alone how many seat would those voters have been able to flip if they all voted for the same party together it might seem simplistic but it gave us some seat that were not considered to be crucial seed that might flip or change end and it I lighted them to us it I lighted 676 seats half of wit half of which were labor half of which were conservative and when you looked at all the labor seats they were all labor stronghold who had been stronghold since the 50s since the 30s even but when you looked at the conservative seats it words all seed that they want two or three elections ago so the Conservatives see quickly become likely to us as the more likely to change end and it led us to the sidelines that there was a good chance that tourism a majority would be dent and obviously we had the different local reporters who worked with us cover report on this this was the front page from the UM and I we actually had trouble finding a partner a national partner for that story because it was going a bit against what was being told at the time but we partner ended up as a small piece in the time but I think it's a good example of joining the statistics community the open data community together to create the model the new voters and then have the journalist report on it with a strong background in this I'm done yeah I speak too much sorry thank you

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