1. Civic Tech Cities: researching US government inhouse technologies

    Today, mySociety, in partnership with Microsoft, launch Civic Tech Cities, a new piece of research looking at the technologies local governments implement to serve and communicate with their citizens. You can download it here.

    Civic Tech: whose job is it?

    Debating and making decisions on behalf of the people; managing services, disseminating information — all of these have been the agreed tasks of local government for a very long time. But has citizen-facing technology now also become a core function of government? And if so, how are they doing?

    We often say that mySociety was originally set up to show governments how they could be using digital better, and that one day we hope to have done ourselves out of a job.

    But perhaps it’s wrong to foresee a time when we’ll be able to pack up and go home. Perhaps those within government will never be able to escape internal bureaucracies and budget constraints to provide the software that their citizens will really benefit from; perhaps the provocative NGO, one step ahead with citizen-to-government technologies, will always be a necessary agent.

    We won’t know for sure until we start researching beyond our own sphere.

    A vital new area for research

    When we set up the mySociety research programme, as you’d expect, our first priority was to look at the impact of the services we, and other organisations like us, were providing.

    Around the same time, the term ‘Civic Tech’ was gaining traction, and it carried with it an implicit reference to applications made outside government, by organisations like us, cheekily providing the tools the citizens wanted rather than those the government decided they needed.

    If our aim was to wake governments up to the possibilities of digital, to some extent it has been successful. Governments around the world, at all levels, have seen the financial and societal benefits, and are producing, buying in, and commissioning civic software for their own online offerings.

    It is, then, high time that the sphere of government-implemented civic technologies were more closely examined: how effective are they? Who is using them? What changes are they wreaking on the relationship between citizen and government? How, indeed, are governments themselves changing as a result of this new direction?

    Civic Tech Cities

    Thanks to generous funding from Microsoft, we were able to conduct research that seeks to answer these questions, in the context of municipal-level council digital offerings in five US cities.

    Emily Shaw, in collaboration with mySociety’s Head of Research Rebecca Rumbul, examined standalone projects in Austin, Chicago, Oakland, Washington DC and Seattle, to produce case studies that cast a light on the state of institutional civic tech in the current age.

    The technologies chosen for scrutiny were diverse in some ways, but the challenges they faced were often alike: and we can all, whether inside or outside government, recognise common pitfalls such as failing to budget for ongoing maintenance of a service that was expected to roll happily along, untended, for the foreseeable future; or building a world-changing digital service that fails to gain traction because its potential users never get to hear about it.

    It’s our hope that local governments everywhere will benefit from this in-depth look at the tools US municipal governments have put in place, from LargeLots in Chicago which sold disused land in disadvantaged neighbourhoods for a nominal $1 fee, to RecordTrac in Oakland, a request and response tool for those seeking information under California’s Public Record Act.

    Better tools make better policy

    Interestingly, one of the key findings of this report is that developing digital tools alongside policy, rather than bolting these tools on afterwards, results not only in better tools, but better policy too.

    The user-centred design principles that have been central to the Civic Tech movement had a knock-on effect beyond the software development departments of municipal government. They began to shape the ways in which policy itself was developed, resulting in services that were more accessible and appropriate to the communities they serve.

    Two-way learning

    Finally, it’s not just governments who will learn from this examination of best practices, potential problems and unexpected bonuses; we, and other NGOs like us, can gain crucial insights from the sector which, after all, is pursuing the same aim that we are.

    You can read the research paper here. Many thanks to Microsoft for making it possible, and to Emily Shaw for putting in the time and effort to make it a reality.

    Image: Jindong H

  2. Looking forward to Florence

    It’s just a few days now until our annual research event, TICTeC.

    The Impacts of Civic Technology conference is an opportunity for researchers, activists, funders, and all the other people that make up the ever-growing Civic Tech sector, to come together and learn from one another in two days of inspiring presentations and workshops.

    In between sessions, the odds are very much in favour of conversations with people whose area of expertise is precisely relevant to your own — that’s one of the primary reasons, attendees tell us, that they enjoy TICTeC so.

    And that’s before you even throw in the fact that we’ll be convening in one of the most beautiful cities in the world: Florence, Italy.

    The agenda is looking great: you can see it here, and more details about the speakers are here. It’s always a sign of a good event when the team members putting the website together are already talking excitedly about which sessions they hope to attend!

    If all of that is making you wish you had booked a place, well, it’s not too late. There are a very few tickets left so if you act now, you could still be joining us in the Villa Vittoria for the highlight of the Civic Tech year. There are even a few free tickets available, so please email gemma@mysociety.org if you’re interested.

    If you can’t make it, don’t forget to follow proceedings on Twitter via the @mySociety Twitter page and via the #TICTeC hashtag. We’ll also be producing videos of the main plenary sessions which we’ll publish on the TICTeC website after the conference.

    Ci vediamo presto!


    Image: Villa Vittoria

  3. What I learned from 20,000 dog poops

    When working with data that you didn’t set out to gather you have to be careful to think about what the data actually means, rather than what it seems to be saying. As an example, one of the “interesting” side effects of FixMyStreet is a database of places people have reported dog poop (or “dog fouling” as it tends to be called academically). We now have over 20,000 locations across the UK where nature’s call has both been heard, and reported.

    My first thought when learning about this data was “that’s a lot of dog poop!” but it turns out 20,000 dog poops is not a lot of dog poop at all. There are an estimated 8.5 million dogs in the UK, assuming (on average) each one poops once a day, they’ll produce over 3.1 billion poops a year.

    So actually, 20,000 poops over nine years is nothing compared to the amount of pooping going on. But just because our data is a drop in the bucket doesn’t mean we can’t learn interesting things from it. The first question to ask is if we have a representative sample of where all this dog fouling is going on. The answer, sadly, is no. But the reasons for that answer raise further questions – which is interesting!

    When you map the location of dog poo complaints in England against the Index of Multiple Deprivation [1], you get this:

    FixMyStreet Dog Fouling Reports

    This tells us that reports about dog fouling are roughly parabolic – there are more in areas in the middle than those that are either very deprived or very not.

    This is interesting because when Keep Britain Tidy actually went out into the world and checked (p. 14), they found this:

    LEQSE Dog Fouling

    This graph tells a very different story, where dog fouling gets worse the more deprived the area. But why is this? And why doesn’t our data tell the same story?

    One reason we would expect more dog poop in the most deprived areas is that the most deprived areas are more urban. Taking the same IMD deciles and using the ONS’s RUC categories to apply a eight point ‘ruralness’ scale (where 1 is ‘Urban major conurbation’ and 8 is ‘Rural village and dispersed in a sparse setting’) lets us see the average ‘ruralness’ of each decile. While this reflects that deprivation is spread across urban and rural areas – the most deprived areas tend to be more urban.

    Ruralness vs IMD Decile

    As urban areas have fewer natural places to dispose of dog waste, and the most deprived areas are more urban, we would expect the most deprived areas to have more dog fouling.[2] We also know that measures that contribute to IMD scores (such as crime levels) are related to trust and social cohesion in an area.[3] When social cohesion is lower, we would expect more dog fouling because owners feel less surveyed and are less concerned with the opinion of neighbours. The real world increase reported by the Keep Britain Tidy survey supports these relationships.

    The drop off in our reported data compared to the real world can be explained by features of the general model for understanding FixMyStreet reports — some measures of deprivation are correlated with increased reports (because they relate to more problems) and others with decreased reports (because they hurt the ability or inclination of people to report). We would also expect areas with worse deprivation to have fewer reports because of disengagement with civic structures.

    Quickly checking the English dog fouling data (so only 17,103 dog poops) against the same model confirms that significant relationships exist for the same deprivation indexes as the global dataset with the largest effect size of a measure of deprivation being for health – as health deprivation in an area goes up, reports of dog fouling increase.

    What this tells us is that our dog data (and probably our data more generally) is clipped in areas of the highest deprivation. We’re not getting as many reports as the physical survey would suggest and so our data has very real limits in identifying the areas worse affected by a problem.

    This is a lesson in being careful about interpreting datasets you pick up off the ground – if you used this data to conclude the most deprived areas had a similar dog poop problem to the least deprived areas you would be wrong. Because we have an independent source of the real world rate of problems, we can see there is a mismatch between distribution in reports and reality. Using this independent data of ‘actual problems’ for one of our categories makes us more aware that there is negative pressure on reports in highly deprived areas.


    If you’d like to learn more about the history of dealing with dog poo on the street (and who wouldn’t want to learn more about that!) – I’ve very generously gone into more detail here.

    [1]: An index that combines thirty-seven indicators from seven domains (income, health, crime, etc) to provide a single figure for an area that is indicative of its level of deprivation relative to other areas.

    [2]:This is relative. Rural areas still have problems with bagged dog poo (“the ghastly dog poo bauble” hanging from branches – as MP Anne Main put it). There is also a risk to the health of cows from dog fouling in farmland – so there are unique rural dog poo problems.

    [3]: Ross et al. found “People who report living in neighborhoods with high levels of crime, vandalism, graffiti, danger, noise, and drugs are more mistrusting. The sense of powerlessness, which is common in such neighborhoods, amplifies the effect of neighborhood disorder on mistrust.”

    Header image: https://www.flickr.com/photos/scottlowe/3931408440/

  4. OGRX: sharing the best in Civic Tech research

    At the Impacts of Civic Technologies conference TICTeC last year, we were treated to a presentation on a resource for the Civic Tech research world. OGRX, the Open Government Research Exchange is a repository of digital, eGov and Civic Tech peer-reviewed and stand-out articles, out of GovLab NYU — you can see the in-depth presentation here.

    As one of the featured Editors of OGRX, mySociety’s Head of Research Dr Rebecca Rumbul was recently invited to make her top five picks from the collection. As she explains, her selection runs from the “paper that should be read by all newcomers to the Civic Tech world” to the “important piece of literature that I take inspiration from when designing my own research projects”.

    Rebecca has this to say about the value of sharing other people’s research in the sector, and the benefits of OGRX:

    Rebecca Rumbul“The mySociety research team spends lots of time asking interesting questions about Civic Tech, and dreaming up ways to answer those questions, but one of the main things we do that is not so obvious is read about other people’s research. A LOT!

    “Before we start any new research project, we carefully review what others have done before us, thinking about what worked for them, what kind of experimental design they used, what other writers inspired their research, and what insights they were able to draw from their work. Learning about others’ research is one of the main parts of the job of researching the impacts of Civic Tech.

    “This is one of the reasons that we began the annual TICTeC conference: to give practitioners and researchers interested in the impacts of Civic Technology a genuine opportunity to learn, share and challenge each other in a safe space.

    “Alas, TICTeC only happens once a year, and outside of that, it can be tough to know where to go to find interesting, current and relevant research, especially if you don’t have university access to online journal articles.

    “That’s where OGRX really fills the gap. If you are thinking of submitting something for TICTeC and want some inspiration, or if you are just interested in accessing good quality and relevant content, why don’t you have a look around? You can also submit your own research!”

  5. FixMyStreet: Why do some areas report more than others?

    I’m just a few weeks into my position of Research Associate at mySociety and one of the things I’m really enjoying is the really, really interesting datasets I get to play with.

    Take FixMyStreet, the site that allows you to report street issues anywhere in the UK. Councils themselves will only hold data for the issues reported within their own boundaries, but FixMyStreet covers all local authorities, so we’ve ended up with probably the most comprehensive database in the country. We have 20,000 reports about dog poop alone.

    Now if you’re me, what to do with all that data? Obviously, you’d want to do something with the dog poop data. But you’d try something a bit more worthy first: that way people won’t ask too many questions about your fascination there. Misdirection.

    How does it compare?

    So, starting with worthy uses for that massive pile of data, I’ve tried to see how the number of reports in an area compares against other statistics we know about the UK. Grouping reports into ONS-defined areas of around 1,500 people, we can match the number of reports within an area each year against other datasets.

    To start with I’m just looking at English data (Scotland, Wales and Northern Ireland have slightly different sets of official statistics that can’t be combined) for the years 2011-2015. I used population density information, how many companies registered in the area, if there’s a railway station, OFCOM stats on broadband and mobile-internet speeds, and components from the indices of multiple deprivation (various measures of how ‘deprived’ an area is, such as poor health, poor education prospects, poor air quality, etc) to try and build a model that predicts how many reports an area will get.

    The good news: statistically we can definitely say that some of those things have an effect! Some measures of deprivation make reports go up, others make it go down. Broadband and mobile access makes them go up! Population density and health deprivation makes them go down.

    The bad news: my model only explains 10% of the actual reports we received, and most of this isn’t explained by the social factors above but aspects of the platform itself. Just telling the model that the platform has got more successful over time, which councils use FixMyStreet for Councils for their official reporting platform (and so gather more reports) and where our most active users are (who submit a disproportionate amount of the total reports) accounts for 7-8% of what the model explains.

    What that means is that most reasons people are and aren’t making reports is unexplained by those factors. So for the moment this model is useful for building a theory, but is far from a comprehensive account of why people report problems.

    Here’s my rough model for understanding what drives areas to submit a significantly higher number of reports to FixMyStreet:

    • An area must have a problem

    Measures of deprivation like the ‘wider barriers to housing deprivation’ metric (this includes indicators on overcrowding and homelessness) as well as crime are associated with an increase in the number of reports. The more problems there are, the more likely a report is — so deprivation indicators we’d imagine would go alongside other problems are a good proxy for this.

    • A citizen must be willing or able to report the problem

    Areas with worse levels of health deprivation and adult skills deprivation are correlated with lower levels of reports. These indicators might suggest citizens less able to engage with official structures, hence fewer reports in these areas.

    People also need to be aware of a problem. The number of companies in an area, or the presence of a railway station both increase the number of reports. I use these as a proxy for foot-traffic – where more people might encounter a problem and report it.

    Population density is correlated with decreased reports which might suggest a “someone else’s problem” effect – a slightly decreased willingness to report in built-up areas where you think someone else might well make a report.

    • A citizen must be able to use the website

    As an online platform, FixMyStreet requires people to have access to the website before they can make a report. The less friction in this experience makes it more likely a report will be made.

    This is consistent with the fact that an increased number of slow and fast home broadband connections (and fast more than slow ones) increases reports. This is also consistent with the fact that increased 3G signal in premises is correlated with increased requests.

    Reporting problems on mobile will sometimes be easier than turning on the computer, and we’d expect areas where people more habitually use mobiles for internet access to have a higher number of reports than broadband access alone would suggest. If it’s slightly easier, we’d expect slightly more – which is what this weak correlation suggests.

    Other factors

    Not all variables my model includes are significant or fit neatly into this model. These are likely working as proxy indicators for currently unaccounted for, but related factors.

    I struggle, for instance, to come up with a good theory why measures of education deprivation for young people are associated with an increase in reports. I looked to see if there was a connection between an area having a school and having more reports on the basis of foot-traffic and parents feeling protective over an area – but I didn’t find an effect for schools like I did for registered companies.

    So at the moment, these results are a mix of “a-hah, that makes sense” and “hmm, that doesn’t”. But given that we started with a dataset of people reporting dog poop, that’s not a terrible ratio at this point. Expanding the analysis into Scotland and Wales, analysing larger areas, or focusing on specific categories of reports might produce models that explain a bit more about what’s going on when people report what’s going wrong.

    I’ll let you know how that goes.

    Image: Dave_S (CC-by/2.0)

  6. What Do We Know about the EU Referendum?

    Just in case you missed it: a little while ago we had an itty bitty referendum on whether the UK should stay as a part of the EU.

    Given that this has had a small, barely worth talking about really, hardly noticed it impact on British politics, we wondered whether there would be any visible changes in the way that people are using our Freedom of Information site WhatDoTheyKnow.

    Did people suddenly find themselves wanting to know more about Europe-related matters in the run-up to the referendum? What about afterwards?

    Short answer: Yes they did! To both questions!

    Long answer: Same as the short answer…but with graphs!

    What we did

    First we drew up a list of twenty-three keywords which might indicate that the request was at least partly related to either Europe, the EU, or the topics that became part of the debate leading up to the vote: keywords like EU, European Parliament, Schengen, refugee, and, that brave little neologism that could, Brexit*.

    Then we pulled all requests where the requester had used one or more of those phrases** and started number-crunching.

    What we found

    In the period between the May 2015 general election and the June 2016 EU referendum WhatDoTheyKnow sent 1,022 FOI requests that matched our EU keywords. These were generated by 641 unique requesters.

    Looking at these requesters: 79% of them made just a single request, and 96% made four or less. The remaining 25 users made 25% of all EU requests — with three users making more than 20 requests each.

    For the year leading up the election there was an average of 55 users making 75.6 EU-related requests between them each month.

    If we split this into two halves (the last half of 2015 and the first half of 2016), the average number of users per month had increased by 20 in 2016 compared to the second half of 2015 — with a peak in both users and requests in the month before the referendum and a decline in the immediate run-up.

    run-up-eu-requests

    So people had more questions to ask once the referendum was more in the public eye. But maybe that’s just reflecting wider trends across the board. Can we state with certainty that this change was referendum-related?

    Let’s move on to the second question: What happened after the referendum?

    After the referendum

    Comparing the three months before the referendum with the three months after it, we see users and requests are up in the post referendum period.

    EU-related requests Users making EU-related requests
    Pre-referendum 310 216
    Post-referendum 332 252

    Looking month-by-month, we can see this is mostly an immediate spike followed by a drop-off:

    eu ref - either side

    In fact when we looked week-by-week, we could see the largest spike was in the week following the vote. This gives us some definite hints that it was the referendum that was driving this.

    But to make extra sure that this increase really was referendum-related, we compared these changes to the overall WhatDoTheyKnow trends at the time.

    The number of requests made across the platform increased between the two periods (17,246 increased to 19,120) — but there was also a decrease in the number of unique users making requests (4,850 decreased to 4,721).

    This means the post-referendum increase in EU requests was counter to the general flow – and we can use a statistical test (chi-square) to confirm that the difference in users making EU requests is sufficiently different from the overall direction of users to reject the idea they are being driven by the same trend (p < 0.01 for those that want to know) .

    So we can say there is a real difference before and after the referendum: people were asking government for more for more EU-related information after the referendum than before it.

     Notes

    *First appearance in an FOI request: May 2015!

    **Obvious Complaint: But Alex! Aren’t some of those a bit broad? And the answer is yes! In fact we discarded ‘immigration’ and ‘migration’ as keywords because when separated from other keywords, these were mostly requests for information about immigration rules relevant to the requester (although that said, a similar post-referendum peak appears when we looked at these ‘immigration’ requests in isolation. There were just too few to make as big a deal out of the change).

    ‘EU’ as a keyword will similarly be catching requests that have nothing to do with the EU, as EU law is so integrated that appeals to directives or other obligations can make an appearance in requests to just about any public body on just about every topic.

    While the global count of ‘EU related requests’ might be inflated by this, a change relative to the population of all requests (like the one we found) should be robust — assuming that non EU-related requests that mention the EU are not distributed differently to non EU-related requests that don’t. This seems reasonable and so for the sake of this blog post — let’s say that’s so.

    Keywords used

    Here are the words we used (note on why we didn’t include ‘immigration’ or ‘migration’ above); one request often matched multiple keywords:

    Term

    Matches

    European Union

    112

    EU

    780

    European Commission

    22

    EU Law

    44

    European Law

    9

    European Parliament

    18

    EEA

    446

    European Economic Area

    30

    European regulations

    1

    EU regulations

    9

    European directive

    1

    EU directive

    7

    Asylum Seeker

    25

    Refugee

    79

    Resettled

    7

    EU migrants

    5

    European migrants

    2

    EU nationals

    16

    European nationals

    3

    Schengen

    9

    Calais

    9

    Brexit

    46

    EU Referendum

    75


    Image: Speedpropertybuyers.co.uk (CC by/2.0)

  7. InfoLib’s Impact

    Researching in an unstable environment

    It’s been nearly two years since the InfoLib Liberia project with iLab Liberia started. In that time the project has faced many hurdles, some predicted, and some completely unforeseen.

    The iLab team have seen their country devastated by Ebola, only 11 years after the end of their second civil war, bringing tragedy and instability along with it. As you can probably imagine, the impact of curfews, fear and death in communities has made it difficult for people to continue with their daily lives. The social impact of such a disease is wide-reaching. Distrust, marginalisation and exclusion can be directed at those who show symptoms, or even who suffered and survived.

    These are challenges that our local partners have had to contend with every day, both when holding training sessions and more crucially when researching the impact of the project on people’s lives.

    However, by far the largest hurdle for this particular project has been a mixture of low internet penetration and lack of government will to release information. The team on the ground have been working tirelessly to create an ecosystem of requesting and training Public Information Officers (PIOs) to reply – even providing them with tablets to scan documents without needing electricity, let alone a computer. But if those officers have no access to the information that has been requested, their jobs become virtually impossible.

    The project is now drawing to a close and we’re undertaking our final research survey. It seemed like a good time to take a look at what we’ve learnt about the impact of our joint Freedom of Information project in Liberia.

    Results

    When designing the project we decided that impact could best be measured in terms of whether or not the project increased confidence in government transparency.

    We carried out surveys in January 2016 and April 2016, to provide a baseline picture and then an assessment of impact at midline. The final survey is being conducted in August 2016 just as the project ends.

    The first survey – the baseline – was carried out mainly in the rural areas. iLab Liberia teamed up with LFIC to survey 152 participants who had been involved in the FOI workshops that LFIC had held in the counties.

    We had to attempt the second survey twice, as it turned out to be more challenging than we’d expected. We needed the participants from the first questionnaire to answer the same questions we’d asked them initially, in order to measure change — but it proved hard to locate all of them.

    There were many factors which caused this, but the main one was economic drivers, forcing people to move to where the opportunities are. It’s a problem many researchers must run into working in the field.

    Carter, the project lead at iLab Liberia told us:

    “There are several reasons why this happens […]. People migrate a lot between markets, farms. Several persons who participated in the baseline could not be reached as they [had] travelled to other cities/counties. [Or] the job that allowed them to reside in that city/county is no longer available so they might have left seeking after another job.”

    Our second attempt was more successful. We managed to contact a large percentage of the original participants in the survey: 112 of the 152.

    internetaccessliberiaWe’ve found out some interesting things from doing this research. We saw that 74% of people who use the internet daily say it’s their main source of information, though it is still only a small percentage of the population who have access to the internet.

    So the next biggest source of information? Radio! 85% of people with with no access to the internet give radio as their main source of information. Thinking of the migration of workers between cities and counties – you suddenly appreciate why Radio is such an important medium for getting hold of information. Thankfully, as you’ll remember from our original blog post, we’re covering both of these media in the InfoLib project.

    In the months since we began studying the impact of this project we also learned that fear of making a request has dropped by 5% in the individuals surveyed . The amount of people who reported that they didn’t know how to ask for information dropped from 24% to 21%. This is pretty great news to us as it shows that our training and our encouragement is working – albeit slowly.

    govtransparencylibFinally we saw the percentage of people who believe government would be more transparent if citizens could see the information they hold rise by 3% to 93% of the surveyed respondents. Even if this figure hadn’t risen, this demonstrates a clear existing demand from the citizens of Liberia for the Government to release more information about its activities which is great news overall!

    Challenges

    No project is without its challenges, and as you’ve seen above one of the big ones is ensuring that the same people respond from survey to survey. Not being able to pin down precisely the same set of people means that we can’t say with 100% certainty that we have a true measure in the difference in attitude.

    As a result of the economic and social drivers mentioned above, the workforce in Liberia is very transient. This makes disseminating information through radio and internet mediums even more important. This research has shown that these are the primary sources of news and official information for the majority of Liberians, and continuing to improve knowledge about, and access to, information via these sources will empower the population further.

    Finally, it can be challenging to demonstrate impact in projects like these, simply because research is not the main focus for our local partners. We partner with local groups because they are passionate, capable, and able to engage and mobilise citizens around a certain issue. We cannot expect small grassroots groups to have the resources or experience to conduct academic surveying, sampling or interviewing that could detect and definitively isolate the short term impact of a small project. This piece of research has provided some encouraging interim results, but most of all, it has provided valuable lessons to us at mySociety in trying to conduct this kind of impact research remotely and in partnership.

    While we wait for the outcome of the final survey we can feel cautiously hopeful that this project has caused a small change in the way access to information operates in Liberia. infoLib will continue to run after the project officially ends, and mySociety will continue to support the work that iLab does in this area . However it may take longer than we had expected or hoped, to see the governmental shift towards releasing information.

  8. What People Want To Know on WhatDoTheyKnow

    mySociety’s flagship Freedom of Information (FOI) request portal WhatDoTheyKnow.com, operating in the UK since 2008, has amassed a whopping 330,000 FOI requests (and counting) from citizens over its eight year life-span.

    That equates to approximately 15-20% of all FOI requests made in the UK. It also represents the largest database of FOI requests in the country, having provided a platform for requests and responses to over 17,000 UK public authorities to be published publicly online.

    Those are some impressive numbers: however, until now we haven’t known much more about what requests are being made, whether there are trends, or indeed, whether the responses that people are receiving are satisfactory.

    We thought it was about time that we took a look under the bonnet of WhatDoTheyKnow to find out the answers to some of these bigger questions.

    Subject matter

    We decided first to look at what themes and policy areas people were most interested in when making an FOI request. We chose this area because we suspected that many people would be asking for similar things from similar authorities. If this is the case, then this would be a clear evidence-based argument for authorities to increase pro-active publication of certain information.

    The task itself was not an easy prospect. WhatDoTheyKnow does not have a tagging or categorising system, so there are over 330,000 requests that we had no quick or easy way of comparing. The volume of data was also so high that we couldn’t reasonably extract every request and analyse which policy area(s) it was relevant to.

    To solve this issue, we decided to focus on the 20 authorities receiving the highest volume of FOI requests between 2008-2016. This way we could rely on a large sample of requests for both both local authorities and government departments. The list of authorities is below.

    Department for Work and Pensions

    6,841

    Department for Education

    1,974

    Home Office

    5,381

    Wirral Borough Council

    1,953

    UK Borders Agency

    3,377

    Birmingham City Council

    1,582

    Brighton & Hove City Council

    3,367

    Liverpool City Council

    1,538

    Transport for London

    3,111

    Westminster City Council

    1,501

    Ministry of Defence

    2,859

    HMRC

    1,476

    Metropolitan Police Service

    2,515

    Bristol City Council

    1,301

    Ministry of Justice

    2,372

    Lambeth Borough Council

    1,296

    BBC

    2,310

    Camden Borough Council

    1,290

    Department of Health

    1,989

    Kent County Council

    1,235

     

    Taking all the requests made to these public bodies gave us a total of 49,500.

    With the generous support of Thomson-Reuters, we were able to use OpenCalais, their automated tagging system, to assign one or more thematic tags to each FOI request made. Over 100,000 hyper-granular tags were automatically applied in this way.

    Once that was complete, we went through each tag and the requests it was associated with. We grouped tags into policy areas and checked for any that had been incorrectly assigned. We then split the authorities into two groups: Local Authorities and Departmental Bodies, to compare the most requested information.

    Among Local Authorities, the top requested information concerned:

    1. Housing Specifically, information on social housing stock/occupancy/waiting lists, facilities for homeless and at-risk individuals, and planning permission
    2. Social Care Information concerning care providers and their funding/operations, care in the community arrangements, social worker qualifications and staffing levels, and information concerning the operation and monitoring of social work departments
    3. Accounts and Budgets Citizens commonly request accounting and budgetary information at a far more granular level than authorities are currently publishing.
    4. Authority management Citizens also wish to know with greater detail how authorities are operating internally, requesting management and meeting information, emails about decision-making, and structural information concerning development, contracting and relationships with private companies
    5. Business rates Concerning long-term empty properties, the impact of rates on town centres, charitable or other discounts, and regeneration.

    These are the top five of thousands of tags, but common themes were clear when comparing these authorities.

    Generally, requesters have shown they want information in a more detailed form than authorities are currently providing, in particular in the expenditure of public funds and those services catering for complex cross-cutting social issues. Given the ongoing housing crisis in the UK,  coupled with the ageing population, it is likely that information concerning these policy areas will be in increasing demand.

    Conversely, among Departmental Bodies, the top requested information showed few common themes. This is primarily due to the differences in policy areas between the departments. There were, however, significant spikes in certain policy areas within departments, particularly around immigration, and this will be the focus of future investigation.

    In conclusion, we understand that very few FOI requests are completely identical in subject matter, but broad trends are clearly evident.

    If Local Authorities proactively publish more granular information about the policy areas we now know citizens are actively interested in, they may see a dip in formal FOI requests.

    Publishing information and data in a machine-readable format may even enable other civic technologists like ourselves to build tools to assist councils in their delivery of vital services. Whilst this will not eradicate FOI requests completely, it would hopefully begin a shift in behaviour.

    In short: wouldn’t it be great if, instead of authorities seeing FOI as an administrative burden, they began to see pro-active publication as an opportunity to harness the skills, initiative and flexibility of citizens.

     

    Image: Allison McDonald (CC)

  9. Do authorities respond faster by email or through an FOI website? Our latest research

    When you send a Freedom of Information request through a site like WhatDoTheyKnow, do authorities respond in the same way as to a request sent via email? Our latest research would suggest that there is a small but crucial difference.

    Just one channel

    We provide Alaveteli, the software that underpins Freedom of Information sites all over the world — but of course, those sites are not the only means by which citizens can make FOI requests.

    A Right to Know means that citizens can request information via whatever means are allowed in their country’s law: traditionally, that’s by post, but many authorities will accept requests via phone and email, and there are even examples of responses being obtained via Twitter.

    So Alaveteli sites make a complicated and potentially intimidating process easier, and they also have the benefit that they publish requests and responses online for everyone to access, but they represent just one channel via which information can be accessed.

    Something that we’ve often wondered is whether there is any difference in the way authorities respond via an Alaveteli site, or via the email system.

    An experiment

    So mySociety’s research team got together with Informace Pro Všechny, the Czech Republic’s Alaveteli site, to conduct an experiment.

    The question under scrutiny: Are Freedom of Information requests sent via email treated the same as requests sent via an Alaveteli platform that allows citizens to make requests via an online portal, and publishes all responses publicly on its website?

    We wanted to know:

    • Would responses be the same?
    • Would it take the same amount of time to get a response?
    • Would you overall get a better or worse service via Informace Pro Všechny than via a personal email address?

    These questions are especially pertinent to us because we want to make sure that our technology is working for people, rather than against them. At the very least, we want to ensure that using an Alaveteli platform such as Informace Pro Všechny will provide the same level of service that citizens can expect from using private email addresses. If using a site such as this does not result in the same level of service, then this would be an issue we as civic technologists should know about and try to address.

    Our experiment was simple. We sampled 100 public authorities (town halls and ministries), and sent them two separate requests via a private email address, and two separate requests via Informace Pro Všechny.

    The information requested was deliberately simple and uncontroversial, and clearly subject to Freedom of Information law, to avoid any deliberation by public authorities about whether to release it.

    Findings

    The good news is that using both channels of communication — individual email or Informace Pro Všechny — results in the same quality of response. Neither method of communication was found to be inferior to the other with regard to how substantive the response was.

    The even better news is that use of Informace Pro Všechny resulted in faster responses to requests. Whereas private email requests were provided on average within 9.2 days, responses to requests sent via Informace Pro Všechny took only 7.2 days – two days quicker.

    This is a positive outcome that was by no means certain, and at this point we are unable to fully explain it. It is possible that public authorities were quicker to respond to Informace Pro Všechny requests because these were known to be published online, and therefore, a slower response would be more noticeable.

    Or the quicker response rate via the site could be attributed to the fact that its users are known to be politically active, politically interested or involved in journalism: a quicker response might reduce negative coverage or feedback. Or it could be that other external factors we were unaware of influenced the result.

    More research would be required to determine the causes of these differences, however, at this point, we are simply delighted to say that Informace Pro Všechny is currently the quickest tool to use to request information from government in the Czech Republic.


    Image: A pre-Czechoslovakia dissolution stamp, from 1966. Most FOI responses are much quicker than this, by post or other means. Karen Horton (CC)

  10. Discussing impact in Barcelona: TICTeC 2016

    The chairs have been stacked, the banners rolled away, and 142 delegates have returned to their 29 home countries. TICTeC, the Impacts of Civic Technologies conference, is over for another year.

    The 1.5 day event saw a concentration of wisdom and expertise from across the civic tech sector, and we’re keen to ensure that we share as many insights as possible.

    To that end, we’ll be publishing materials such as photos, videos and slides, as soon as we can. We hope that, if you weren’t able to attend, they’ll give you a taste of the TICTeC experience — and, if you were there, they’ll serve to keep it fresh.

    Some materials will take a little time: videos, for example, are currently in post-production, and should be ready within a few weeks. We’ll be announcing on the mySociety Twitter feed, Facebook page and this blog when they’re online, or check the TICTeC resources page.

    Meanwhile, here’s what’s available right now:

    • Slides from all the speakers Click on each speaker’s name to access them.
    • Photos: all under Creative Commons, so feel free to download and share them if you wish.
    • A Storify to help you relive the experience through hashtagged tweets and photos.
    • The TICTeC Google Group: everyone who attended the conference is a member, so this is the place to continue discussions or begin new ones.

    Thanks so much to everyone who participated, making TICTeC a real success. We hope to see you all again.