1. What happened to all the APPGs?

    Over Easter, some groups went missing in Parliament.

    No, not lost tourists: of the 722 All Party Parliamentary Groups registered in March, only 444 are left – a 39% decrease in the space of a month. What caused this, which groups have been removed, and what happens next?

    Tl;dr: we’ve published the changes as a spreadsheet.

    What is an APPG?

    All Party Parliamentary Groups (APPGs) are self-selecting groups of MPs and Lords with an interest in a particular policy area. Browsing the list might help you find out that you have more in common with MPs than you think; subject-based APPGs include Craft, Jazz, and Parkrun, and country APPGs range from Albania to Zimbabwe. Most groups are supported by a secretariat, which is usually a charity, membership body or consultancy organisation.

    The logic behind APPGs is to create legitimate avenues for experts and interested parties from outside Parliament to discuss policy with MPs – but unfortunately they can also be vehicles for corruption. As  Transparency International argue: “While APPGs can help inform debate, time and time again we see examples of MPs and Peers exercising poor judgement by accepting all-expenses-paid trips from regimes with highly questionable records on corruption and human rights.”

    Why were so many groups removed?

    New rules came into place on 31st March 2024 that required:

    • Increased financial reporting 
    • A ban on funding from foreign governments
    • Increased reporting on secretariat support 
    • A minimum of 20 members 
    • Exactly four officers, two of whom must be MPs

    How did the Register change?

    Parliament maintains the Register of all APPGs that gets updated approximately every six weeks. The last edition before the rule change, published on 6th March 2024, showed 722 groups in total – 130 country groups and 592 subject groups. The 8th April edition shows 444 in total – 74 country groups and 370 subject groups. In total, 39% (278) groups were removed, with the countries list shrinking by 43% and the subjects list by 38%.

    Why does this matter?

    We don’t know exactly why each group was removed from the register. In some cases they simply may not meet the new 20 member threshold, but in others, deregistering might be an attempt to evade scrutiny.

    Deregistered “unofficial” groups can operate in very similar ways to registered APPGs (and there is some evidence they are already doing so) but will not have to abide by the same rules. This means that the only way to track the activities and spending of these groups, and the outside interests that fund them, is through individual Members’ Registers of Financial Interests. Parliament’s rules are clear that MPs are supposed to declare all benefits received through group membership (whether or not a group is an official APPG) but in practice this can be inconsistent.

    Which groups were removed?

    We’ve published the full list of groups from the last two registers, the changes, and the list of removed groups as a spreadsheet.

    What next?

    TheyWorkForYou has a long history of making MPs financial interests data easier to access and understand. We make it easier to see changes in MPs’ declarations over time and are now publishing this information as a big spreadsheet

    We have a lot more work in the pipeline around both APPG data and Register of Members Financial Interests data (stay tuned for details in our newsletter).

    If you think what we’ve done so far is valuable, and want to help us go further: please donate

    Photo by Zetong Li on Unsplash

  2. Council Climate Action scorecards support climate officers

    Lucie Bolton took the position of Climate Strategy Officer at Rother District Council in 2022. Since then, she’s found the Council Climate Action Scorecards project an invaluable support for her work. 

    Hearing this, we were of course keen to find out more — so we asked Lucie to share her journey, from brand new climate officer to now, a couple of years on, with a refreshed strategy and action plan in place.

    “The council had declared a Climate Emergency in September 2019, going on to adopt their Environment Strategy in 2020”, explains Lucie, “But the pandemic and staff changes meant the production of a Climate Action Plan was delayed. That’s not to say climate action wasn’t taking place, but there were no KPIs, and it wasn’t fully embedded across the organisation.”

    “Scorecards helped us reimagine both our content and project design.”

    Post pandemic, recognising a need for a more concerted approach, the council employed two new staff: Lucie as Climate Strategy Officer, plus a new Climate Project Officer.

    “I was brought in to refresh the Environment Strategy — which was renamed the Climate Strategy — and to develop and deliver the Climate Action Plan.”

    While Lucie had highly relevant experience in her background, the council context was new for her: 

    “I came from an environmental NGO, where I was involved with developing strategies, but I hadn’t developed a Climate Strategy for a local authority before. 

    “I performed the usual strategy development activities — gap analysis, evidence base and so on — and when I was looking at best practices across the sector, I came across the Council Climate Plan Scorecards.”

    The Climate Plan Scorecards, released in 2022, were the precursor to the Climate Action Scorecards. They scrutinised every UK council’s action plans, marking them to a wide set of criteria. 

    “This was a fantastic resource for me,” says Lucie, “as I was able to see what good looks like and what we should be aiming for. 

    “I used the Scorecards to look at neighbouring authorities, authorities with similar emissions, demographics et cetera. Along with other resources like the UK100 Powers in Place report, it helped me shape the Rother District Council Climate Strategy. 

    “I was also able to reach out to different authorities and speak to their Climate Officers, which was useful.”

    In 2023, the Council Climate Action Scorecards were launched, providing Lucie with still more invaluable data.

    “I found the methodology particularly useful for developing Rother District Council’s Climate Action Plan. It was also useful to benchmark against, to see what we have already achieved and where we could do better”. 

    “This was a fantastic resource for me, as I was able to see what good looks like and what we should be aiming for.”

    “Overall, the results were useful in demonstrating to colleagues the sort of things we could be doing and what our neighbouring authorities were doing.”

    Rother District Council adopted the refreshed Climate Strategy and Climate Action Plan in December 2023, and Lucie continues to dip into the Scorecards.

    “I am now using them regularly in the implementation of the Climate Action Plan. For example, we have an action to eliminate pesticide usage in the council’s grounds maintenance. Using the Scorecards, I can quickly find examples of other councils who have already done this, and access the information I need through the evidence links.

    “I’m really pleased to hear there will be another round of council scoring. I think Rother District Council will score better thanks to the action we have taken since the first round of scoring, though I am concerned the timeframe will mean some significant activities will still be in progress. Our new Local Plan, for example, is aiming to be ambitious and align with our 2030 target, but is unlikely to be ready to be examined in that round.”

    Thanks very much to Lucie for sharing her story. We hope it inspires other Climate Officers to explore how the Scorecards project can aid them in their work.

    Image: Chris McAuley (CC BY-SA 2.0, via Wikimedia Commons)

  3. 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. 

  4. TICTeC keynote speaker announcement: María Baron

    We’re excited to announce the first keynote speaker for our 2024 Impacts of Civic Technology Conference (TICTeC)!

    Join us on 12 and 13 June  — in London or online — and you’ll hear from María Baron, founder and now Global Executive Director of Directorio Legislativo.

    This year, one of the major themes at TICTeC will be the role of civic tech in safeguarding and advancing democracy where it is under threat. María and Directorio Legislativo’s work explore both  the problem, and how we can collectively roll up our sleeves and do something about it. 

    María has a long career in transparency and democratic institutions, working first across Latin America and then globally with both Directorio Legislativo and the Open Government Partnership. Along the way, María also founded the Latin American Network for Legislative Transparency, convening 24 civil society organisations from 13 countries. 

    With her team at Directorio, María developed a methodology for building consensus across polarised stakeholders on tricky issues — and has brought many of those agreements to Congress, where they were signed into law.

    The Regulatory Alert Service, also from her Directorio team, enables political analysts to predict changes in regulation across 19 countries. 

    Among many other achievements, María has been awarded the NDI Democracy Award for Civic Innovation. In short, we can guarantee you’ll gain a massive dose of inspiration and hope from her session.

    And that’s just the first speaker announcement from this year’s TICTeC. Make sure you’re a part of the “best concentration of practitioners, academics, and thinkers in this field” (Fran Perrin, Indigo Trust) and book your place now.

    It’s been a while since we convened the wonderful, industrious, inspiring global civic tech community in one place, face to face — we’re ready to reignite those amazing conversations, connections and deep dives into democracy at the Impacts of Civic Technology Conference, this June. 


  5. “Don’t be afraid to copy” and four more highlights from the Scorecards Successes Conference

    To reach the UK’s 2050 net zero target, all local authorities need to take serious action across all of their operations. But what exactly should they do, and in what order?

    To get the most out of the brilliant data uncovered by the Council Climate Action Scorecards, Climate Emergency UK commissioned Anthesis to research and write a report digging into the characteristics that were associated with high marks. This allows campaigners and officers alike to go to their councils and say: “Start here. These are the most effective actions to drive up our scores, and reduce our carbon footprint.”

    The Scorecards Successes report is available to read now, and it was an absolute pleasure to join councillors, campaigners and others in the climate sector yesterday for a really encouraging conference to celebrate its launch.

    Here are five things I took away:

    1. Good governance generates great scores

    As you can see from the table above, appointing a climate portfolio holder is the most impactful characteristic for high scores in the Council Climate Action Scorecards. I loved the way Matt Babic from Anthesis (authors of the report) described effective governance as a T-shape, with the downstroke representing depth of knowledge within a climate team, and the across stroke representing good communication and distribution of responsibility across the council as a whole. For campaigners out there, this might be a good way to start a conversation with your local council  — how effective  is your council’s climate ‘T’ in depth and breadth? 

    2. Funding reform is vital

    The report recognises that since 2019, councils have spent more than £130 million applying for short term competitive funded pots; time and money that is wasted if they are unsuccessful. This came up time and again throughout the day, and there was consensus across the room. In order for councils to be able to deliver at the pace and scale necessary, national government needs to unlock these barriers to funding and enable clearer, simpler financial mechanisms, which must also facilitate necessary private sector investment. 

    3. Devolution deals need simplifying if they’re going to support better climate action

    One surprising finding from the report is that authorities that are members of Combined Authorities score lower on the whole than those that are not. This paints a mixed picture for the successes of devolution deals in delivering across their constituent councils. In the final panel of the day, Sandra Bell from Friends of the Earth and co-chair of the Blueprint Coalition, gave some excellent food for thought about the future of devolution deals across the UK. The UK government has promised devolution deals “everywhere” by 2030, which is also the date by which many UK councils have committed to reach net zero. We still lack clarity on the exact form and shape of the deals yet to come, and with a very mixed picture of multiple types and styles of devolution settlements currently in operation, the Blueprint Coalition are calling for clarity, simplicity and scaled up funding to help this new layer of governance really deliver. 

    4. Transparency and public engagement aren’t the same thing, but they’re both needed 

    At mySociety, we care a lot about transparency, and we’re always asking for better data publication to enable it. Better data publication from local authorities would enable us to make useful climate data more accessible to those who want to dig into it. But publishing data and engaging the public aren’t entirely the same thing. In addition to transparency, councils should be actively delivering public engagement exercises that tackle  the more holistic questions and future decision-making, about how to make the road to net zero a fair one. It was great to hear Cllr Anna Railton talk about Oxford City Council’s residents panel – a great forum for these conversations, and markedly cheaper than a citizens’ assembly. Transparency and public engagement are related, but not the same, and we need both.

    5. “Don’t be afraid to copy”

    Rob Robinson from Kent County Council made the point that I think underpins a lot of why we think the Scorecards are so helpful. Every council in the UK is working towards net zero, be that to their own target or the UK’s 2050 target, but they don’t have to do it alone. In every section there are high scoring councils, and the evidence of the brilliant policies they’ve implemented are easily discoverable on the site. Let’s not reinvent the wheel: this isn’t an exam, as Rob says —  don’t be afraid to copy.

  6. 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.


    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.


    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.

  7. Guest post: What are the questions MPs ask that don’t get answered?

    This blog post is part of our Repowering Democracy series. We are publishing a series of short pieces of writing from mySociety staff and guest writers who are thinking about how our democracy works and are at the frontlines of trying to improve it.

    This week, we’re re-publishing a blog post from Anna Powell-Smith at the Centre for Public Data, which is a new, non-partisan non-profit working for stronger public data. We’re previously worked together on recommendations to avoid fragmented public data. This blog post touches on several issues close to our hearts: Parliamentary written questions, and where there isn’t enough data to understand what’s going on.

    Data gaps are under-reported, because it’s hard to write about data that doesn’t exist.

    As we’ve written about before, newspapers publish endless stories on house prices, where there’s lots of data – but few on rental costs, even though millions of people rent. That’s partly because the Office for National Statistics doesn’t collect much data on rentals.

    To tackle this problem, I’ve been thinking about how to map data gaps, and make them more visible.

    And I think the best way is actually to think about questions, instead of data. What are the important questions that the government can’t answer?

    Obviously, ‘important’ is subjective! But one source of clearly important questions is Parliamentary written questions, which are the formal questions that MPs and peers ask the government. Where the government doesn’t have the data to answer them, it has to say so.

    So this post introduces new research: a data analysis of 200,000 Parliamentary written questions, and what they tell us about the UK’s missing numbers.

    Our modest goal: to find the UK’s biggest data gaps.

    What we did

    Building on some previous research of ours, we strapped on our coding hats 🪖, and did the following:

    • First, we scraped all the written questions in Parliament from December 2019 to February 2023, from TheyWorkForYou, which gaves us about 200,000 questions.
    • Next, we flagged questions asking for quantitative information, with phrases like “how many” or “how much” – which showed that about a fifth of questions wanted data, just under 40,000.
    • Then we flagged questions where the government apparently said the data was “not held”, “not collected”, etc. About a quarter of quantitative questions were answered like this.

    And we ended up with a dataset of around 10,000 questions where MPs apparently both (i) asked for data, and (ii) were told it was not available. So: missing numbers.

    Then we spot-checked the questions to check our method. It wasn’t perfect, but it was very decent. (It helps that Parliament uses formal, consistent language.) You can download the full dataset here.

    Sometimes, MPs ask about strange things, like jobs for clowns. But most are extremely serious, covering the issues that affect MP’s constituents. And overall, they tell us what MPs need to know.

    Data gaps by department

    Firstly, we looked at how often each government department said that data wasn’t available. (See the code.) And there were were huge differences:

    • At the Department of Health & Social Care, around 40% of quantitative requests were unanswered (though we can cut them some slack, as this was during the Covid pandemic).
    • At the Home Office and the Department for Work & Pensions, around a third were; at the Ministry of Justice the proportion of unanswered quantitative requests was 30%, and the Department for Education 27%.
    • But the proportion was much lower at other big departments – almost all others were below 20%.

    Of course, we need to be cautious here, as the numbers are approximate. Without reading each question, we can’t be sure that we’ve tagged it correctly, or if the MP was asking something impossible. It’s probably most useful to consider the differences between departments.

    Given that, it’s not surprising that the health, benefits, justice and education departments would get requests for data, since they run massive operational services that affect people’s lives. (The Foreign Office, by contrast, largely seems to get asked about wine.) It’s more surprising that they seem to struggle to answer them more than other departments.

    Now let’s dive into what these unanswered questions were about.

    The topics with the biggest data gaps

    Each question scraped has a title. We can use this to see which topics were least likely to get an answer.

    Other than Covid-related topics, the major topics with the highest proportion of unanswered questions were:

    1. Benefits – grouping together benefits like Universal Credit and PIP
    2. Asylum, refugees and migrants
    3. Child maintenance
    4. Energy meters
    5. Armed forces housing

    This seems plausible. The DWP Select Committee has repeatedly criticised the government for the lack of visibility over the benefits system; the statistics regulator has expressed concerns about the use of asylum statistics, while the National Audit Office has noted gaps in the data available on smart meters.

    We also used GPT-4 to try tagging questions, which worked quite well. We used it to tag questions to the Department of Health & Social Care. This helped us identify major clusters of unanswered questions in these areas.

    In healthcare, MPs often struggled to get basic prevalence information, whether:

    Also, funding is a topic it’s surprisingly difficult to get information about, e.g.

    Following on from this, hospital-level information in general often seems to be poor, e.g.:

    And finally, workforce is a huge one, with topics like:

    You can see the tagged questions here – there are many more examples under each topic.

    This gets really worrying when you look at the dataset over time. It’s immediately clear that MPs often ask the same thing over and over again – yet the information doesn’t seem to improve.

    What next?

    We think statistics producers should be monitoring Parliamentary questions, to tell them where data needs to be better. After all, MPs deserve answers to their questions, and so do we all.

    If you can help us make this happen, we’d love to talk.

    If you’re interested in this research – or even better, if you can fund us to do more of it! – please do get in touch.

    Image: Tom Chen on Unsplash.

  8. Council Climate Action Scorecards help councillor to get a sustainability motion passed

    We were more than delighted when this news story crossed our radar, showing in detail how Cllr Andrew Murray, of Newry, Mourne and Down District Council, used the Council Climate Action Scorecards to gain support from his fellow councillors for climate action.

    Cllr Murray’s proposed motion even referred to the Scorecards themselves:

    “This Council acknowledges the work done to date to help address the climate emergency; reaffirms previous motions regarding the degenerating global situation; and again, reiterates that the crisis is the biggest threat posed to our constituents, our district, and our planet.

    “Further acknowledges, however, that recent data collated by Climate Emergency UK ranks NMDDC 8th out of the 11 Councils within NI; and thus, pledges to include ambitious targets in the forthcoming Sustainability and Climate Strategies and Action Plans to expedite implementation.

    Cllr Murray went on to explain that the council was below the averages for Northern Ireland in five sections of the Scorecards, albeit that in two — Building & Heating and Waste Reduction & Food – they had scored better than most of their NI fellow councils. Finally, he pointed out that their scores may have suffered from a lack of communication around the council’s recent activity.

    We admired this intervention for its use of the Scorecards to do several things: point out where the council was lagging behind others in the country; give recognition to the areas where Scorecard rankings were above average; and to point out that some action they were taking may not be visible enough to outside observers.

    All of these points were given further legitimacy by the fact that the Scorecards are an independent project, providing an objective set of benchmarks.

    We got in touch with Cllr Murray to ask him more. He was a strong advocate for his local area, happy to describe its many charms:

    “I am an elected representative for the Slieve Croob DEA,” he told us, “which lies within Newry, Mourne and Down District Council. I live in a wee town called Castlewellan. We’ve lots of forests, hills and coast within my area, and the council area as a whole.”

    Sounds like an area where it’s well worth protecting the natural environment then! So, how did the Scorecards help?

    Cllr Murray explains: “The Scorecards were very useful. I used them as an impetus to draw up a motion asking our council to attribute targets to actions they are taking, or will take in the future, regarding climate change and the environment. 

    “Because the Scorecards were collated as well as being subdivided into relevant sections, I was able to curate my speaking notes appropriately.

    “But they were also useful for a number of other reasons: firstly, they averaged out what other councils in Northern Ireland were attaining. In Northern Ireland, we have different responsibilities to our English, Scottish and Welsh counterparts. So to have them separated out regionally meant that Council Officers could not simply bat away the motion by saying the cards were not relevant – there are demonstrable things that other councils within Northern Ireland are doing that we are not. 

    “That is not to say that they were simply used as a stick with which to beat Officers! There were aspects in which our council was above average, so this allowed praise to be allocated to the areas in which it was deserved. 

    “Likewise, there were areas in which, from my reading of them and my understanding of the council, I think that there are some functions we are actually already performing but haven’t communicated – ergo, we could easily improve our score. 

    “The Scorecards enabled me to lay things out succinctly and clearly, and I was able to get the motion passed. The hope is that sections of them can be incorporated into the targets for the council, and we can ultimately improve on our climatic and environmental impact. 

    “Obviously if that means we improve our position amongst other Northern Ireland councils, then happy days. But, as the saying goes, an incoming tide raises all boats – so if our position remains the same, but councils everywhere become more sustainable and mitigate our impact on the environment, then that’s a good thing all round. But ultimately, we have to control the things that we affect here in Newry, Mourne and Down District Council.”

    That is exactly what we like to hear, and goes a long way to exemplifying exactly why Climate Emergency UK and mySociety came together to produce the Scorecards project. 

    We are very glad that Councillor Murray was able to use them for furthering climate action in his beautiful corner of Northern Ireland — and we hope councillors everywhere will take inspiration from his method for doing so.

    Image: Shan Marsh Bubashan

  9. Democracy month notes: February

    Previously: January!

    Gaza ceasefire blog post

    I wrote a blog post about the Gaza Ceasefire opposition day votes – especially focusing on how there ended up being no recorded votes. 

    This is the kind of responsive work we’d like to do more of. We don’t need to duplicating every explainer out there, but we want to be able to better articulate “this is how Parliament works, but there’s something wrong with that” when there’s currently something confusing/going wrong in the news. 

    Asking for money to do good things

    Alice, Julia and I have been putting together a more structured version of the idea I talk about at the bottom of this blog post about our new spreadsheet of the register of interests — using crowdsourcing to create good, understandable summaries of MPs interests. Will let you know how that goes. 

    Something we’d like to get better at is being more public when these applications for funding do not work out (spoiler: this happens a lot!). There’s a lot of work and creativity that goes into our ambitions for TheyWorkForYou, and ideally these wouldn’t just be locked away in various virtual desk drawers. 

    Oflog consultation

    Julia worked with our friends at the Centre for Public Data on a joint response to an Office for Local Government (OFLOG) consultation – read more about that

    This is a continuation of our work around public data fragmentation

    Small API updates

    Matthew has added Parliament’s unique identifier to the response to the ‘getMPInfo’ API call, making it easier to jump from our data to query the Parliament API.

    Server upgrades

    Sam and Matthew have been upgrading the servers that run TheyWorkForYou and WriteToThem.

    We need to do this periodically for security reasons: the organisations that distribute the server software (and other packages we depend on, like those that distribute the programming languages) only provide security and bug fixes for a certain period, after which they only provide it for newer versions. 

    Running software on the web — where there are *constantly* bad people testing for weaknesses — means taking this seriously. But upgrading the lower levels of the “stack” often means small changes further up where features we use have been deprecated and replaced with other approaches. Some of this work is running just to stay in the same place, but it does also enable us to adopt new approaches in how we code and the packages we use. 

    This is one of the massive benefits of the same organisation running TheyWorkForYou AND WhatDoTheyKnow AND FixMyStreet AND (many more) – we have excellent people thinking hard about our technical infrastructure across all our work. 

    Voting summary update

    We’ve done some of the trickiest technical work required to enable the voting summary update we’re planning.

    We’ve moved TheyWorkForYou from pointing at the Public Whip website, where it used to get voting summary calculations, to an instance of a new,experimental “twfy-votes” platform. This is doing the work Public Whip was originally doing, but also taking over the party comparison calculations that were being done in TheyWorkForYou itself previously. 

    TheyWorkForYou has become simpler, and more of the relevant code is now in the same place. We’re not yet completely independent of the Public Whip because twfy-votes currently uses the database dump to populate itself — but soon we’ll be able to move that to an export from TheyWorkForYou’s own database. 

    The goal in this set of changes is to move from this:

    Diagram showing the flow of data from the Hansard XML, through Parlparse, into both TheyWorkForYou and the PublicWhip - with that then reentering theyworkforyou and additional calculations being done to calculate voting summaries

    To this:

    Diagram showing the different flow of data from the Hansard XML - through ParlParse to TheyWorkForYou, and a feedback look between TWFY and TWFY-VOTES

    Which is… still a lot of boxes and arrows, but is better than it was. This could in principle then be simplified even further, but this brings the whole process under our control and simplifies some of the back and forth steps. 

    Currently, all this work should have resulted in almost no visible changes to the site. But we now can flip a switch and it will switch the underlying algorithm used from the one in the Public Whip to the new (simplified) approach.  One of the motivations behind this shift is to be fully in control of that algorithm (which is effectively a number-based editorial policy). 

    One of the things I’ve been doing this month is running the analysis to clearly map what exactly the public effect of this will be. Broadly, most things stay the same, which is good because we don’t want the headline messages to be hugely affected by different methodologies behind the scenes – At the same time we’ll end up with something that is easier to explain. 

    The final stage before full release is a set of less technical changes, consolidating the voting summary information on one page, and adding a rewritten page describing both how Parliamentary voting works in different places across the UK, and what our approach is in the data we publish. Making good progress on these, and hope to have this project completed soon. 

    That’s all for now

    As ever, if you’re the kind of person who reads to the end of these (I’m going to assume a generally nice person who is also a fan our our work) – donations are welcome. But also get in touch if you’ve got something to chat with us about!

    Header image: Photo by yasin hemmati on Unsplash

  10. Climate monthnotes: January & February

    It’s so tempting to start each of these with a clichéd “where did the time go?” or “how is it X month already?”, but in this case, it really does feel like 2024 is running away from us! 

    January kicked off with Louise, Alex and I heading to the Democracy Network conference, where the theme of climate ran throughout lots of the discussions. If you are also interested in the intersections between climate, democracy and civic tech, you’ll be delighted to know that the call for proposals TICTeC 2024 is out now!

    At the start of February, Annie from Climate Emergency UK and I worked on a piece that was published in the LGC, responding to an article from Richard Clewer asking for more emissions data in the Council Climate Action Scorecards. We agreed with Richard that more scoped emissions data would strengthen the scorecards. But, without a statutory reporting framework, that data simply doesn’t exist. We pointed to our fragmented data asks, that I’ve written about in these parts before. Also on our fragmented data work, our joint response with the Centre for Public Data to the Housing & Levelling Up inquiry has been published on the committee’s website. Two great examples of collaborative working to kick off the year!

    The big ticket item for the last few months has of course been the Local Intelligence Hub, our joint project with the Climate Coalition, which launched to the public on 15th February! We’ve had such brilliant feedback from the launch, including great coverage in national and local media outlets. Zarino and I have been demonstrating the Hub to anyone who’ll have us (get in touch if you’d like your own demo!) — or watch Zarino’s brilliant short videos on YouTube. Struan and Alexander have been working through the datasets at phenomenal speed, and Myf has been doing wonderful messaging on Twitter and over on LinkedIn.

    There are plans afoot to add even more data, so if you’re sitting on datasets that you think would be useful to yourself and others as part of the Hub, let us know! We’re especially interested in data organised by the new constituency boundaries, which I explain in more detail in a blog post about the recent byelections. Zarino made the most of the extra leap year day with several of our friends from the sector, at an event about data and the new constituencies.

    Alongside all of the excitement about Local Intelligence Hub, the wheels are starting to turn for the next round of the Climate Action Scorecards. Siôn, Zarino and I have all attended different section-specific roundtables, which have involved brilliant discussions with council officers and industry experts. I’ll be joining the CE UK team at the Scorecards Report Launch & Conference on the 21st: hope to see some of you there! 

    Photo by Chandan Chaurasia on Unsplash