1. Scorecards volunteering increases climate skills, knowledge and confidence

    The Council Climate Action Scorecards are compiled by a cohort of volunteers, trained up by Climate Emergency UK. They’re currently recruiting for the next round of marking, so if that sounds like something you’d like to be involved with, check out the details here.

    The knowledge that volunteers acquire isn’t just applicable to the Scorecards: it upskills them for life, empowering them to apply their knowledge to informed climate action. In that way, the benefits of the Scorecards project are more longlasting, and spread further than we might have expected!

    Fiona Dyer was part of the volunteer cohort of 2023, and she shared her journey from climate-concerned to climate-informed. Her story can inspire us all — especially those who may be feeling powerless or hopeless in the face of the climate crisis.

    Fiona explains: “At the start of the COVID pandemic I had to retire early from the NHS to look after my mum. I had more time to read, and the more I read, the more concerned I felt about the impact global heating and biodiversity loss was going to have on my children’s future. Across the world people were already suffering. 

    “I heard about the CE UK Scorecards project from a friend, and decided volunteering would be something positive I could do that I could fit around my other commitments. I doubted whether my computing skills would be adequate, but the CE UK team was friendly and supportive, and we volunteers learnt from each other via a chat forum. 

    “Reading through councils’ climate action plans to find information was challenging at times, but it also gave me a good understanding of the scope, powers and potential influence councils have to help communities mitigate and adapt to the challenges that lie ahead.” 

    So, that’s where it started — but it’s certainly not where it ended! Fiona goes on to tell us how she could bring that acquired knowledge to a whole new arena.

    “I went on to join Climate Action Durham (CAD), and learned that they’d held a Citizens’ Forum on Climate Action the year before, in collaboration with Durham County Council. 

    “I suggested we used the Scorecards at the next forum, as up to date, publicly available research that would give us a better understanding of the breadth of topics councils should be addressing, as well as performance data. 

    “It was agreed that by using the Scorecards we could more easily assess the council’s climate response plan: its strengths and weaknesses, how it compared with similar and neighbouring councils and how we could gauge improvement over time. 

    “The citizens’ forum was held in the autumn, timed to be just after the publication of the Scorecards. As we had already established a ‘critical friend’ type relationship with the council, it was agreed that the introduction to the forum would be given by myself, alongside the council’s Neighbourhoods and Climate Change Corporate Director. 

    “My presentation was a combination of some of the council’s own slides and slides I created using Scorecards data, chosen to highlight issues that would help focus discussion in the work groups that followed. 

    “I would not have had the confidence to do this without my experience of being a Scorecards volunteer, as I have no previous experience in this area. It was also an opportunity for me to champion the broader agenda of increasing local democracy. “

    That’s the increased confidence that knowledge can bring. And then, as Fiona explains, the event itself was enriched and informed by the Scorecards data.

    “The Citizens’ Forum on Climate Action was open to anyone who wanted to attend. People were asked to choose the work group they wanted to be part of in advance: these broadly aligned with the Scorecard categories and they were given the link to the Scorecards website. 

    “The questions and scores in each of the Scorecards categories enabled us to be more effective in scrutinising the council’s performance. 

    “The council said they welcomed CAD’s involvement in consulting the public on its climate plans and being held to account in a constructive way.”

    And from this one day emerged some longterm outcomes:

    “The feedback from the forum work groups was written up in detail as a report, including nine specific recommendations. Where possible I used my Scorecards knowledge to cite examples of good practice by other councils for each recommendation, these were included as footnote references. 

    “For example, Bristol use an Eco Impact Checklist that is applied to all their new projects. This report was shared with the council and made available to the public via the CAD website. 

    “CAD members who facilitated the groups in the forum have continued to work with the relevant councillors, to varying degrees, as the next iteration of their climate plan is being developed. We will see how many of the recommendations are included in the new plan when it is published later this year. 

    “As a group we intend to continue supporting, lobbying and campaigning where it is needed. We have just set up Durham Climate Hub, part of a national network of climate emergency centres and are continuing to work with the council’s community engagement officer. In the run up to this year’s forum we plan to hold sessions in the Hub on some of the forum themes to increase interest and participation from a broader section of the public. 

    “I have suggested CE UKs training to various other groups, one of which I have co-hosted with CE UK using my local knowledge. It feels good to be playing my part in raising awareness of the challenges we face and working creatively with other people to improve local resilience, not forgetting the bigger picture and fundamental need for system change.”

    Fiona’s account is a phenomenal example of how citizens can work together with their local councils to understand, oversee and encourage better climate action. It shows how the Scorecards training has a ripple effect that is tangible and longlasting. 

    Big thanks to Fiona for sharing her experience — we hope it will inspire others who are looking for a way to take practical and productive action on climate issues.

    Image: David Ross

  2. Access to Information community of practice: an in-person gathering

    mySociety is currently helping to support knowledge-sharing between organisations and individuals who run Access to Information projects around the world, in a community of practice.

    Several such folk were in London for our TICTeC conference last month, providing a perfect opportunity to come together in person and share insights.

    Representatives of Access to Information sites from around the world

    Matt Stempeck of the Civic Tech Field Guide has written the discussions up in full (he also deftly explains the slight difference, terminology-wise, between Freedom of Information and Access to Information) and you can read his account here.

    Meanwhile, here are the top-line topics that were under discussion:

    • Logistics How do you facilitate a community of very busy people, spread across multiple countries and speaking different languages — and how do you ensure that interventions are timely and productive? The group discussed which types on online communication and touchpoints work best for them; how to ensure topics are relevant to their immediate needs; and on which platforms it’s possible to talk about challenges just as freely as successes.
    • Measuring impact Are there consistent metrics we could be collecting across all ATI projects to demonstrate and compare impact? What are the individual issues experienced by each project that impede the collection of such metrics?
    • Governments What are the issues that groups face within different countries, with differing levels of governmental tolerance towards ATI?
    • Engagement How do projects educate the public about their rights to information, and encourage more of them to use these rights?
    • Journalism How can ATI projects work with newsrooms or individual journalists to discover stories and, incidentally, also help spread awareness of ATI? In which ways does the ATI process not fit well with journalists’ needs?
    • Funding One area where the network can offer useful peer support is in swapping notes over where they source funding, and other potential channels of income. Some funders were also present, and so were able to give their valuable perspectives too.

    If any of these topics spark your interest, hop over to Matt’s account for the full details.

    mySociety is supporting the international Access to Information community of practice alongside the Civic Tech Field Guide, Access Info Europe and Open Knowledge Germany.

    Banner image: James Cameron

  3. New in Alaveteli: request categories

    Alaveteli is our platform that anyone can use to run a Freedom of Information site in their own country or jurisdiction.

    As the number of requests grows on an Alaveteli site, it can become increasingly difficult to find released information that you’re interested in.

    You can search, but the more general the term, the more likely that you’ll pull in results where the term is mentioned incidentally rather than being directly related to the information released. Or you can browse by authority, but that’s more fiddly when you want the same information from a range of authorities.

    There’s also the issue that people new to FOI might not have a clear idea of what to ask about. Freedom of Information is great because you can ask for anything, but as a newcomer that can feel overwhelming. You need some direction to know where to start.

    Request categories allow us to curate related requests to bridge the gaps mentioned above.

    Here’s an example of a category on WhatDoTheyKnow that compiles successful Freedom of Information releases related to the British Post Office scandal.

    British Post Office scandal on WhatDoTheyKnow

    Categories can be created in the admin interface via the Requests > Categories menu item.

    Request categories work in a similar way to the current public body categories – in fact, as part of this development we’ve revamped the underlying code so that it applies to both!

    At their core, they’re composed of three things – the title, body (where we can add explanatory content), and requests grouped by a tag.

     

    Notes can be added to call out key information, and categories can be added to headings to create a layer of hierarchy. As part of this development, we’ve also improved notes so that they can be more easily styled with some preset colours, and added rich text editing to improve the formatting of longer notes.

     

    We’ve started building up some interesting categories of requests on WhatDoTheyKnow, but we’d love to hear which ones you’d like to see.

    If you’re interested in how the development unfolded you can take a look at the related work on GitHub.

    Banner image: Garmin B

     

  4. New in Alaveteli: explore CSVs in Datasette

    CSV is a great format for releasing sets of structured data in response to Freedom of Information requests. Indeed, on WhatDoTheyKnow we’ve seen several thousands of CSVs released.

    We’ve recently added the ability to explore CSV files via a Datasette instance. Here’s an example.

    Opening the CSV in Datasette makes it easy to explore and analyse it in an interactive website.

    If you’re not familiar, Datasette converts the CSV to an sqlite database, which means you can then query the data using SQL.

    Alaveteli uses the publicly available lite.datasette.io instance by default, but you can host your own instance and configure it at theme level like we’ve done for WhatDoTheyKnow.

    You can see the implementation details at mysociety/alaveteli/#7961.

    Banner image: Joshua Fuller

  5. New in Alaveteli: importing & presenting blog posts

    Alaveteli is our platform that anyone can use to run a Freedom of Information site in their own country or jurisdiction.

    We’ve added new functionality that allows Alaveteli sites to highlight blog posts on the homepage, so they’re more visible. In this way, Alaveteli sites can not only help users with the ‘how’ of making an FOI request, but also show, in a very tangible way, the ‘why’  — especially if the posts are highlighting impactful uses of the site.

    Previously, Alaveteli had a basic way to pull in an RSS feed of blog posts. These were only available on the blog page (/blog), which often does a disservice to all the great work that gets written about.

    We wanted to better signpost the blog from other pages in Alaveteli to celebrate great FOI use, and help users understand how a seemingly simple FOI can go on to have an outsized impact.

    When the site runner configures a blog feed, posts are pulled into Alaveteli and cached in the database. This makes them available on the homepage. Here’s what that looks like on WhatDoTheyKnow:

    Latest News and Campaigns screenshot

    They’re also visible in the admin interface via the Tools > Blog Posts menu item.

    Blog posts lists on Alaveteli

    At present only the title, URL and publication date are cached in Alaveteli. These records are intended to be “pointers” to the canonical URL of the article hosted on the external blog service.

    In the admin interface, blog posts can be tagged to indicate their subject matter.

    As FOI requests and authorities can also be tagged, this allows the blog posts to be highlighted in the sidebar of appropriate pages where there’s a matching tag. So, if someone’s browsing requests or visiting an authority that deals with the climate emergency, for example, they’ll be shown relevant blog posts – hopefully making them more visible to people who have already displayed that they have an interest in the topic, and giving those people a bit more contextual knowledge.

    List of FOI request climate action plans on Alaveteli Climate Action plans on Alaveteli's front end Authority - Geraldine Quango Showing where the related blog posts are on Alaveteli

    In future we’d like to make these posts more visible, by importing header images and a short summary, and give the ability to display some posts when there isn’t a direct tag match.

    You can read about the initial design and subsequent conversation and pull requests starting at mysociety/alaveteli#6589.

    Banner image: Patrick Perkins

  6. How a payslip taught France about their Transparency rights

    Have you ever wondered what the Prime Minister’s payslip looks like? We’re not talking about how much he’s paid — that’s a matter of record — but the actual paper document.

    Over in France,  Xavier Berne from the Alaveteli-based site Ma Dada has just created a bit of a stir by receiving Emmanuel Macron’s fiche de paie in response to an FOI request. This response set off extensive coverage in the French national media on how citizens can use their right to transparency.

    Payslip of President Macron

    Ma Dada were kind enough to talk us through what happened, and how it’s resulted in a better understanding of FOI across France. Developer Laurent Savaete sent us the picture you see at the top of this post, of the front cover of the national paper Libération, which he describes as France’s rough equivalent to The Guardian.

    “Transparency was the front page story”, Laurent says, “which is highly unusual. The next four pages covered transparency, how everyone can use it, and profiles of four power users.” National TV also picked the topic up.

    Just like here in the UK, Macron’s actual salary was already known. The scoop was in receiving the facsimile of the paper document, which came about because Laurent’s colleague Xavier sometimes sends out interesting FOI requests, “for educational purposes, to show that it is possible”.

    Quite by accident, this one actually turned out to be a perfect piece of FOI promotion: because the content of the payslip was nothing new in itself, the media focused on the means by which it was obtained.

    How it happened

    WhatDoTheyKnow dreams of such amazing coverage, and we’re sure that Alaveteli projects around the world feel the same! So, how did it come about, and can other FOI projects replicate these conditions in their own countries?

    Well, we can try, but Laurent reckons that it was broadly down to the planets aligning. As he explains it, “A journalist had been in touch around that time about something else; Xavier happened to mention he’d received the payslip, and she was interested in writing a story. 

    “She is not a long time FOI user herself. To be honest, it was lucky timing — Xavier had just received the response, and the news cycle needed something to break up their coverage of Gaza and Ukraine.”

    If there’s a lesson to come out of this, we think it might be: keep requesting interesting stuff, and keep talking to journalists.

    A spike in new users 

    Because Ma Dada knew the coverage was coming, they had time to put some safeguards in place to make sure the site could handle extra traffic. “We cranked the server up to the max to make sure everything kept running  — which worked across the swell in interest, but we wouldn’t be able to afford keeping it at that level longer term”.

    The peak in visitors may have retreated now, but there’s been an undoubted uptick in usage. “We’ve been seeing a surge in registration for both standard and Pro accounts, and a definite increase on requests being made on Ma Dada for the last two weeks. 

    “We had around 40,000 visitors on the day of story; and 15-20,000 the day after.”

    Reaching the people

    How do you know your media coverage has touched the nation? Well, Laurent was given a nice clear illustration: “The day after the paper came out, I was chatting with the owner of a bookshop in the south of France, and he asked what I do in life, so I said: ‘I work on a project in public transparency’, to which he replied, ‘Oh, they just talked about that on the radio this morning!’. 

    “That radio segment was discussing our publication and mentioned Ma Dada. It was super cool to bump into someone who’d actually heard of us outside of our own dedicated circles.”

    Very cool indeed! And now? Ma Dada are already thinking how they can replicate this great success. “We’re thinking about other documents we might request to get the same amount of publicity again in the future.”

    Best of luck, Ma Dada! Your next story should be received by a more informed general public, thanks to that alignment of the planets.

  7. Parents for Inclusive Education are on a mission — with the help of FOI

    How do you bring about systemic change within structures that are embedded into the national culture? That’s a big question, but it’s one that users of our Freedom of Information site WhatDoTheyKnow are often tussling with.

    One place to start is with data that helps you map the current state of affairs, and FOI can be the perfect medium for getting hold of that. When we spoke to Jack Russell from Parents for Inclusive Education (PfIE), a grassroots organisation of primary school parents in Northern Ireland, he explained the value of data very well: “it means you can start a conversation”.

    So, what are PfIE trying to achieve?

    “We came together because we want to see a more inclusive primary education for every child” – and they’re starting with religious education.

    “We realised that, for many parents, there was a lack of clarity around how RE is delivered in Northern Ireland, and what rights parents have in this area.”

    PfIE wanted to gather data on who comes into schools to deliver RE lessons, collective worship and assemblies. Their aim was to achieve an accurate, representative picture of practices across Northern Ireland, as opposed to their baseline assumptions which, as they admit, had up until then been based on anecdotal evidence.

    From small beginnings

    And so began a large-scale FOI project — although initially the team had much more modest plans: 

    “At first, we were only going to contact our own schools to ask them who was given access and how this was communicated. 

    “But then we realised that other parents might want to be informed about these practices at their schools — and they were entitled to answers too. So we decided to send a Freedom of Information request to every publicly funded primary school in Northern Ireland, apart from special schools: that was 772 in total.”

    The organisation had some tech expertise amongst its members, and, as they explained, at first it seemed that WhatDoTheyKnow wouldn’t quite be suitable for their needs:

    “One of our team — Laura — had successfully used WhatDoTheyKnow in the past to query hospitals about their waitlist times for outpatient appointments, so she suggested using it. But after some initial research, we decided not to, as we’d wanted to include attachments and links in our requests. 

    “I’d written a script to batch send them all, but it turned out that these were heavily spam filtered by the schools’ email server, so we fell back on WhatDoTheyKnow.

    “I’m really glad we did, as the fact that all correspondence will be public is a huge plus for us.”

    Managing batch FOI requests

    So, how did PfIE manage their 772 FOI requests? They signed up for our WhatDoTheyKnow Pro service, which is designed specifically to help keep track of large batches like this, and also allows users to keep their requests and responses private until they’re ready to release their findings.

    “We focused our questions around two areas: first, access: which churches and religious organisations were being given access to schools, and how that access was managed via processes and/or controls; and secondly communication: whether and how parents were made aware of religious visitors; and were informed about the options to withdraw their children from religious practices.

    “We asked 14 questions in total, some of which were yes/no or multiple choice, others which required free-form answers.”

    FOI allows the request-maker to specify the format they’d like to receive their responses in, which can save a lot of data-cleansing further down the line. As Jack acknowledges,”we received submissions back from schools in varied formats, including Word and PDF attachments, and also as plain or rich text email replies.”

    It was all useful, though. “The data we collected provides us with an objective, fully representative sample — we had a 99% reply rate — to gain an accurate understanding of RE practices in Northern Ireland primary schools. 

    “We understand this response level to be unprecedented, according to academics we’ve spoken to who have conducted similar research. Our project is primarily focused on making data transparently available to parents, so from this perspective the 99% number is hugely encouraging. It also means that any aggregate conclusions we draw are as close to being unbiased as possible — we actually have a response rate that is higher than the NI Census 2021 (97%) which people were legally required to complete.”

    Tenacious in the face of challenges

    Getting to this gratifying result wasn’t all plain sailing, though. Jack explained the issues they encountered along the way:

    “Some schools initially mistrusted the FOI request email that came through WhatDoTheyKnow, and didn’t know whether they had to reply. However, a couple of weeks after we sent the request out, the Northern Irish Education Authority issued guidance instructing schools to reply, providing an information document and template response.”

    In any large batch of FOI requests there will be a variety of levels of response, and PfIE came across this too. 

    “There were non-responses, partial responses and responses with an incorrect understanding of the question. Our first technique to remedy these was by following up via WhatDoTheyKnow, which provided alerts and tools which made this very easy to do — another reason I’m very glad we went with the platform!”

    Fortunately, the FOI Act has a provision for dealing with non-responders: referring them to the Information Commissioner’s Office.

    “For persistent non-repliers, we contacted the ICO, who very diligently helped us further encourage schools to respond.

    “But several of the schools that responded late, following an ICO decision notice, sent their responses to our own email account, meaning that the responses didn’t appear on WhatDoTheyKnow. The team at WhatDoTheyKnow were very helpful in adding these: I sent through several batches of .eml files and they made sure they appeared within the conversation.”

    On a mission

    So how will PfIE be sharing their findings? They are launching a report today, On A Mission, with an event at Stormont. They’ve also created an online map to help people explore the data.

    But they’re not stopping there: “After releasing the findings of our report, we plan to create resources and a set of best practices for schools to achieve a more inclusive RE experience for all students. We also plan to engage and empower parents, hopefully promoting a sense of transparency and open dialogue between the school and parental community.

    “Beyond this, we have several other plans to empower parents, increase transparency and improve the education system in Northern Ireland”.

    And that’s how you start to make change

    PfIE have used the mechanism available to them to produce exactly the outcome they were after.

    “The tools provided by mySociety, together with help from the ICO in chasing up the late responders, and the cooperation of the NI Education Authority in doing the same have been invaluable in achieving this level of response,” says Jack.

    “We would definitely recommend WhatDoTheyKnow. The tools have been really useful in managing a large scale request, and the fact that all correspondence will be publicly searchable and visible is invaluable: it adds a great deal of credibility to our research by effectively underwriting our findings with an auditable trail of evidence. 

    “And on top of this, the team have been super-helpful and a pleasure to work with! “

    We’re glad to have been of service. Thanks very much to Jack for talking us through the project. If you’d like to know more, visit the PfIE website, where you can also sign up to their newsletter to be kept informed.

     

    Image: Priscilla Du Preez

  8. Statement on the proposed ICO fine to PSNI

    The ICO have today announced that they intend to fine the Police Service of Northern Ireland (PSNI) for their accidental release of staff’s personal information in August 2023. This data was released in response to a Freedom of Information request made using WhatDoTheyKnow.

    mySociety is a charity; we run WhatDoTheyKnow as a vital tool to help anyone exercise their right to information held by public authorities. We understand the repercussions of a breach like this, which serves to demonstrate that public authorities must be good at dealing with personal information. We welcome the ICO’s emphasis on the importance of robust release processes to ensuring that information that is important to the public interest can be released safely. 

    We take the responsibilities that come with operating a large platform extremely seriously, especially around the personal data breaches that can occur when authorities’ release processes fail. Following this breach, we’ve undertaken a significant programme of technical and process work to play our part in reducing the risks of this kind of incident.

    We’ve developed a new piece of code which analyses spreadsheets as they come in as responses to FOI requests on WhatDoTheyKnow, and holds them for review if they are detected to contain hidden data. The deployment of this code has proven successful and we will be continuing to improve it. In its first three months, this spreadsheet analyser has screened 3,064 files and prevented the release of 21 spreadsheets that have been confirmed to contain data breaches, and 53 which were likely to contain data breaches (around 2% of the files screened in total).

    In an ideal world, such measures would not be necessary; we continue to work with authorities making such releases to help them understand the reasons for data breaches, the potential severity of their impact, and how to avoid them.

    This blog post was updated at 10:04 on 23 May to correct the figures around the number of spreadsheets screened.

     —

    Image: Pietro Jeng

  9. Access to Information network: data visualisation Show and Tell

    Organisations all around the world run Freedom of Information sites based on our Alaveteli platform. There are also sites running on other codebases. Either way, we’re all working to the same goals, and we believe that each site can learn from the others: for that reason, we’ve set up the Access To Information (ATI) network, a place for people who run FOI sites to meet, chat and share experiences.

    Within this framework, there’s the chance for practitioners to pair up and exchange specific skills under a mentorship arrangement — and last week, we heard from GONG in Croatia who have been learning from Georgia’s ForSet.

    ForSet began life as a data visualisation organisation, and these beginnings have allowed them to communicate data from their FOI site as compelling, visual stories: skills that GONG were keen to get to grips with. Sara, project co-ordinator at GONG, told us about working with Jubo from ForSet on data visualisations — and how her learnings will change the organisation’s work going forward.

    Sara explained that they agreed two main goals for this project: firstly, to improve GONG’s data visualisation skills; and secondly, to use data visualisation to promote their FOI site Imamo pravo znati (IPZ) to journalists and general users. They were successful on both counts, not only did Sara learn how to use new methods and tools; but their outputs also brought approximately 50 new users to IPZ, and two additional Pro users (Pro usage is free on the site, but numbers had been stagnant of late, so this was notable).

    So, how did they go about it? The mentorship comprised four stages: data collection, analysis, storytelling and visualisation, with the last being very interconnected.

    1. Data collection

    This stage began with both sides brainstorming potential topics for FOI requests that would be good candidates for data visualisation. An initial set of 12 topics was whittled down to five: local referendums in Croatia; special advisors (Spads) in the Croatian government; local participatory budgeting projects; local support for youth civic education; and local financing of civil society organisations. 

    GONG then sent 575 requests to local and county authorities, from which they received 525 responses — a pretty good response rate, and higher that expected. They didn’t hit many problems, although several authorities asked for the requester’s ID details, and there was one ministry that cited GDPR as a reason for refusing information on Spads. This case has now been referred to Croatia’s Information Commissioner. 

    2. Data analysis

    Jubo and Sara organised the responses they received into spreadsheets: they were looking for an angle or a story among the data, and tidying it up in this way was helpful for making comparisons. Could they find a story in there that aligned with GONG’s mission or advocacy?

    By organising the data in this way, the pair could easily see which data wasn’t really strong enough to take any further, and which lent itself to storytelling and visualisation. At this stage they rejected some of the angles they’d begun with, narrowing their projects down to local referendums, Spads, and lowering the voting age to 16 for the EU elections (this last project is pending; they’ll be launching a campaign in late Spring).

    3. Storytelling and visualisation

    Two pieces of software were used for the visualisations: Canva and Flourish. Sara was already familiar with Canva, as she uses it to create social media graphics; but Flourish was new to her, and she says she is very happy to have these new skills under her belt.

    Flourish allows you to create many different types of visualisations: you upload your data and it is fairly intuitive to create maps, charts, etc. Once these were in hand, they added a call to action for each story, encouraging people to use their FOI site and especially Pro.

    The visualisations

    Local referendums

    For the story on local referendums, GONG had requested from each local authority the number that had taken place; the topics under discussion; their outcomes; and the number of referendums that were suspended due to not being valid for whatever reason.

    They received more responses than expected, and this was also the first time nationwide data had been collected on the subject.

    Map showing where Croatian referendums were successful or otherwise in reaching quorate

    The first angle that GONG wanted to support with their data and visualisations was ‘Croatia needs a referendum law that recognises the importance of local democracy’. 

    The data showed that out of 47 local referendums that had been held, just 25 met the minimum turnout for the decision to be valid. Jubo and Sara mapped these, and paired their visualisations with the argument that a lower bar for turnout would encourage better participation in local democracy – demonstrated with human figures.

    Turnout quorum for a local referendum
    A local press outlet picked the story up, using the data to make their own story: they were the area that had had the highest number of referendums, so that was their focus. 

    Special Advisors

    The FOI requests returned the names of Special Advisors, the areas they were in charge of, and the fees they were receiving. As Sara explained, in Croatia Spads are not straightforwardly employees of the government, but they have a lot of influence, and in some cases receive huge fees.

    It became clear that there are two different types of advisors, under two laws; while each type has different functions, both are called Spads. First, there are external advisors who may or may not receive compensation; and secondly there is another class of Spads who are employed internally. Neither is subject to Croatia’s legislation on conflict of interest.

    Number of SPADS in each Croatian ministry

    A pie chart was put to service to clearly show how much compensation Spads had received. This varied widely from Spad to Spad, but the criteria dictating who received how much is still unclear: it appears to be at the discretion of the individual minister.

    Pie chart showing SPAD payment in Croatia

    In collecting this data, GONG unexpectedly unearthed a scandal, as they revealed one Spad who was abusing public funds. He was fired, along with the minister concerned; this resulted in nationwide coverage for the data; albeit again with the media’s own preferred focus.

    Lowering the voting age

    Sara says that it was a lot of work to find data to support the argument for lowering the voting age to 16 in Croatia. They wanted to show that, while young people see voting as the most efficient political action, it is denied to a large portion of them.

    Proving the absence of something is always tricky, and in this case they were uncovering that there isn’t any research to show that 16 year olds lack the cognitive abilities to vote responsibly. So they focused on other angles: in some EU countries, 16 year olds can vote, and they demonstrated that those countries are doing well in democratic processes: they score highly in the democracy index and have good voter turnout.

    Data visualisations around the voting age in Croatia

    Like many countries, Croatia’s population is ageing, so the young are in danger of being totally ignored. GONG plan to share their findings on social media in a simplified form with graphics cards, and a call to action to show support for the campaign.

    Questions and answers

    Once Sara had finished her presentation, members of the audience were invited to ask questions.

    Q: How did GONG and ForSet work together?

    A: At the beginning, they had lots of online video calls, and later on when the data had come in, they communicated a lot via comments on the spreadsheets.

    Q: It feels like each of these the topics would be applicable almost everywhere: perhaps it will spark other people’s interest to do something similar for their own country. Any advice if so?

    A: The questions asked in the first two sets of FOI requests were straightforward, which led to straightforward answers. The third topic was less so; Sara and Jubo had to go through lots of reports, and often the data from one source contradicted another. Also, an uncontentious topic is likely to result in more responses: something like referendums is politically neutral, unlike spads where the authorities may have reasons not disclose information.

    Q: When you put the requests together, were you already thinking about the format it would be best to receive the data in?

    A: In that respect, the best question is one with a yes/no answer. The reason for excluding many of the initial topics at a later stage was that the answers varied so widely that it was hard to pull out statistics or a simple throughline: you’d be comparing apples with pears. So, for example, when asking how much of a local authority’s budget is reserved for supporting civic education, and how civic education is delivered, the responses could range from “We are in favour of civic education, but leave it to schools”, to “We provide money for civic education and produce our own textbooks”. Meanwhile, some authorities wrote two pages of waffle in the free text box. 

    Q: Did you narrow down the topics before or after you had submitted the FOI requests?

    A: Both. There were 12 topics at the start; they decided which of them were best suited to FOI, then sent requests for five of them. One the answers had been received, they narrowed it down to three.

    Q: Could one make data visualisation about the other two? It’s hard to find ways to show that there’s no information. Saying that 80% of authorities don’t reply is not a very exciting way of showing things.

    A: While it might not fit in with the initial aim of the project, this sort of thing can be a great way to show how well or badly FOI is working in your country. Journalists often can’t get the information they need, so build stories around the fact that there’s no data about such an important issue.

    Q: We’ve seen how much GONG has benefitted from this mentorship. What, if anything, did ForSet get from this?

    A: Sara was so quick and flexible, she was great to work with. ForSet also learned from the project: for example, that it is better when requesting a large amount of data, that is sorted by the public institution, so it’s easier to work with. You can request it sorted in the way that you need for your story, which might be different from how it is in public.

    Also, Canva is such a great tool for visualisations. They’ve now merged with Flourish, so the have advanced data visualisation features. You just have to make sure you choose the right format: the type of charts or graphs that will show your findings the most clearly. 

    Finally, ForSet didn’t know about the topics that Sara suggested, so there was plenty to learn there, plus it was great to see the ways GONG employ to publish their stories on both social media and mainstream media. 

  10. Creating datasets from FOI data

    Responses obtained from a widespread FOI project can be difficult to analyse, until they are sorted into neat datasets. This allows you to make valid comparisons, pull out accurate statistics and ultimately ensure your findings are meaningful.

    In our third seminar within the Using Freedom of Information for Campaigning and Advocacy series, we heard from two speakers. Maya Esslemont from After Exploitation explained how to prepare for an FOI project to ensure you get the best results possible (and what to do if you don’t); and Kay Achenbach from the Open Data Institute explained the problems with ‘messy’ data, and how to fix them.

    You can watch the video here, or read the detailed report below.

    Preparing for an FOI project

    After Exploitation is a non-profit organisation using varied data sources, including FOI requests, to track the hidden outcomes of modern slavery in the UK.

    Maya explained that they often stitch together data from different sources to uncover new insights on modern slavery. She began with a case study showing some recent work they had done, using WhatDoTheyKnow to help them understand the longer term outcomes after survivors report instances of trafficking. This stood as an excellent example of how much work needs to be done before sending your requests, if you are to be sure to get the results you need.

    In this case, After Exploitation were keen to understand whether there is any truth in widely-held assumptions around why human trafficking cases are dropped before they are resolved: it’s often thought that there are factors such as the survivors themselves not engaging with the police, perhaps because of a nervousness around authorities.

    But what are these assumptions based upon? Actual information was not publicly available, so we wouldn’t know if cases were being dropped because of low police resource, a lack of awareness or more nuanced factors. Until the data could be gathered and analysed, the perceptions would continue, perhaps erroneously.

    Before starting, After Exploitation thought carefully about the audience for their findings and their ultimate aims: in this case the audience would be mostly the media, with the aim of correcting the record if the results flew in face of what was expected; but they knew that the data would also be of use to practitioners. For example, charities could use it to see which areas to target regionally for training and other types of intervention.

    They placed FOI requests with police forces across the country, making sure to ask for data using the crime codes employed by the forces: were cases dropped because of ‘lack of evidence’; did they have a status of ‘reported’ but not gone on to exist as an official crime record?

    The project had a good outcome: while some requests had to go to internal review, ultimately over 80% of the forces responded with quality data. The findings were worthwhile, too: general perceptions did indeed prove to be wrong and there was no indication that ‘no suspect identified’ was a result of the victim’s lack of involvement. The resulting story was able to challenge the general narrative.

    So, how can After Exploitation’s learnings be applied to the work of other organisations or campaigns?

    Maya says:

    • Planning, rather than analysis, is the majority of the work;
    • Identify the need and purpose before you even start to pick which authorities to send requests to;
    • Be clear who the audience for your findings is;
    • Consult with other stakeholders to make sure your parameters are really clear.

    Planning

    Before you even begin, make sure your project isn’t asking for data that has already been collected and is in the public domain — this might seem obvious but it’s easy to overlook. Check other people’s FOI requests (you can do this by searching on WhatDoTheyKnow); look for reports, research, inspectorate/watchdog outputs, and data released as part of parliamentary enquiries.

    That said, even if you do find previous data, there is sometimes value in requesting more up to date or more detailed information with a new set of FOI requests. If you see a national report collating data from every council for example, you could do an FOI project asking every council for a more detailed breakdown of what is happening in their region.

    But before sending a batch of requests to multiple authorities, ask yourself if there is a centralised source for your data. If so, then just one FOI request might be enough: for example, homelessness data is already collected by the Depts for Housing, Levelling Up and Communities, in which case one request to them would save time for both you, and more than 300 public authorities.

    Another question to ask before starting off on your project is “what is the social need?”. Does this need justify the resource you will expend? Mass FOI projects can be a bit of a time commitment, but the utility might not just be for your organisation: perhaps you can also identify a social benefit if the data would be of use to other groups, academics or journalists.

    Define your intended audience: will the data you gather be of interest to them? Do you have a sense of what they want? For example, MPs often like to see localised data that applies to their constituencies. Journalists like big numbers and case studies. If you think your findings are important but might have limited appeal, you could consider including an extra question to provide details that you don’t need for your own purposes, but which could provide a hook.

    Next, will the data that you gather actually be suitable for the analysis you want to perform? To avoid time-consuming mistakes, make sure the data you’ll receive is broken down in the way that you need. As an example, suppose you wanted to ask local authorities for details of programmes offered to children in different age bands: you might receive data from one council who has offerings for children ‘under 18 months’ and another ‘under two years old’ — and where units differ, they are difficult to compare and contrast. Be really precise in your wording so there’s no mismatch, especially if your request is going to a lot of authorities.

    Consider, too, whether you can you get enough responses to make your data meaningful: 2,000 people is the figure believed to be representative of the population as a whole. Decide how many responses you ideally need for your purposes — and, in a scenario where not all authorities respond, the minimum you can work with.

    You might want to contact other groups or organisations who could be interested in the same data, and ask if there are details that would be useful to their work.

    As suggested in Maya’s case study, try to use existing measurements where you can: if you shape your requests to the methodology the authorities themselves use to collect the information, such as KPIs or their own metrics of success, these will be much easier for them to supply.

    If you’re not sure what these metrics are, you can sometimes access internal guidance by googling the name of the authority plus ‘guidance’. Alternatively, submit scoping requests to a handful of authorities to ask how they measure success, etc.

    At this stage it’s also useful to decide what quality of data you will include or exclude. For example, if you ask about training materials and one authority says they offer training, but don’t include the actual materials, do you include it in your figures? The more authorities you ask, the more ambiguities like this you’ll normally encounter.

    Think about where and how you will log the data as it comes in. Maya recommended WhatDoTheyKnow Projects as a good tool for extracting data. Whatever you use, you should consider accessibility: can your platform be accessed by everyone you’re working with, across different communities? Especially if you are working with volunteers, it’s important to remember that not everyone has a laptop.

    Also consider the security of the platform: how much this matters will depend on how sensitive the data is, but recognise that Google sheets and many other platforms store the data in the cloud where it could be more vulnerable to abuse.

    After Exploitation take great pains to ensure that their data is accurate. They recommend that each response is assessed by two different people, making sure that everyone knows the criteria so they’re applied consistently; and doing regular spot checks on a handful of cases to make sure they are all logged in the same way and there’s no duplicate logging.

    This is time-intensive and arduous, but if you have other stakeholders they might be able to help with the data checking: for example, knowing that they would eventually place the story with the BBC, After Exploitation were happy to hand this task over to their inhouse data checkers.

    What if things go wrong?

    If you’ve done all the planning suggested above, it’s less likely that your project will go awry, but even if it does, Maya says that there’s always something you can do.

    No or few responses: ask yourself whether you have the capacity to chase no/late replies, and if you still don’t get a response, to refer them to the ICO. If not, consider prioritising the bodies that are most relevant to your work, eg the biggest authorities or those in areas with the densest populations; but be prepared to defend accusations that not every authority had a fair hearing unless you do them all.

    If you know your requests were well worded, but you’re not getting a lot of responses — perhaps because you’re dealing with a contentious issue, or simply because the authorities cash-strapped — you could shift to measuring the types of responses you get. If authorities aren’t able to answer the question, this can often be just as revealing.

    Responses that don’t tell you what you set out to understand: Consider whether there are any alternative angles in the data you do have: are there any additional themes, particularly in any free text fields? Or try a new round of requests asking for more detailed information.

    Responses don’t cover the whole country: If you can’t get data from everywhere, could you narrow down to just one area and still have useful findings? Even the most basic data can set the scene for other researchers or organisations to build on: you can put it out and outline the limitations.

    Results

    The impact of gathering data through FOI can be massively powerful, as After Exploitation’s work shows. They have revealed the wrongful detention of thousands of potential victims of human trafficking when the government were denying it could happen; opened the debate about locking up vulnerable people; and uncovered the flawed decision making in the Home Office on modern slavery cases. It was only through FOI requests that all this information came into the public domain and was picked up by mainstream media.

    Combining different sources of data to create datasets

    Kay Achenbach is a data trainer on the Open Data Institute’s learning team; the ODI works with government and companies to create a world where data is working for everyone.

    Kay shared a case study from the medical field, in which an algorithm was being designed to quickly assess high numbers of chest x-rays. The aim was to automate the process so that people identified as needing intervention would be sent to specialists right away.

    The developers wanted to make sure that different demographic groups weren’t being biased against, a common issue with algorithms built on existing data which can contain previously undetected biases.

    The test material was a set of x-rays from a diverse population, that had already been examined by specialists. They ran them past the algorithm to see if the diagnoses produced were the same as those made by human doctors.

    The doctors’ assessments came from three different datasets which, combined, comprised data from more than 700,000 real patients. As soon as you combine datasets from different sources, you are likely to come across discrepancies which can make analysis difficult.

    In this case, one dataset had diagnoses of 14 different diseases, and another had 15 — and from these, only eight overlapped. The only aspect that could for sure be compared was the “no finding” label, applied when the patient is healthy. That limitation set what the algorithm was asked to do.

    Other fields were problematic in various ways: only one of the three sources contained data on ethnicity; one source only contained data on the sickest patients; another was from a hospital that only takes patients with diseases that they are studying, meaning there were zero “no finding” labels. Two of the sources contained no socio-economic data. Sex was self-reported in two of the sources, but assigned by clinicians in the other, which could also affect outcomes.

    The advice from all this is that you should look carefully at each dataset before you combine them, to see what the result of combining them would be. In short: does it reflect real life?

    Ultimately the researchers found that the algorithm was reflecting existing biases: it was much more likely to under-diagnose patients from a minority group; more likely to make mistake with female patients, the under 20s, Black people, and those from low socio-economic groups. The bias was compounded for those in more than one of those groups.

    Cleaning up datasets

    Once you’ve obtained your datasets from different FOI requests, you’re highly likely to find mismatches in the data that can make comparisons difficult or even impossible — but cleaning up the data can help.

    For example, in spreadsheets you might discover empty fields, text in a numbers column, rows shifted, dates written in a variety of formats, different wording for the same thing, columns without titles, typos and so on.

    Kay introduced a tool from Google called Refine that will solve many of the issues of messy data, and  pointed out that the ODI has a free tutorial on how to use it, which you can find here.