Tag: Data (Page 1 of 2)

Local data for local places can help save lives

This post is based on desk research, conversations with various people in national and local organisations, and a talk I gave at an OpenDataSavesLives meeting. For more Coronavirus stuff that I’ve worked on see the Ada Lovelace Institute’s “Exit Through The App Store“.

Coronavirus is a pandemic. For a couple of centuries we have known that data is one of the most powerful tools in a pandemic. The UK prides itself on being a world leading nation in the use of digital, technology and data. Yet in England, the largest of the UK’s four nations, we are struggling to get data to local places so that they can use it to help save lives.

The role of local places in a pandemic

In England local authorities are responsible for public health in their area. They also play a vital role across many services including housing, business support, health and social care. They work with a range of partners to do this. Hospitals, doctors, care providers, police forces, charities, businesses and citizens (through both existing and new structures). 

At the moment England can see the end of the first wave of the pandemic and is starting to relax lockdown measures. The focus has shifted to what is called test, trace, and isolate. Widespread testing to understand where the disease is, contact tracing to track down who else might have it, and isolation to contain new outbreaks of the disease.

These are tasks where national decisions and health research play a role, but a similarly important role is played by local places.

Having good data about the spread of the virus in local places might help a community group to tailor hygiene advice to meet language needs, a business organisation to distribute hand sanitisers to shops, care homes to take extra precautions, public health officials and statisticians to produce local predictive models, or a local authority to manage a local lockdown.

Local organisations are often the most appropriate organisations to do this because their staff know their places and the people who live there. They are trusted, or not, in different ways than the central government.

Data and information about the pandemic

But to take these decisions they need information.

Some of this information will come from these organisation’s connections with their places – a community organiser might hear of an outbreak because a friend is affected by it, or people might see complaints about shop hygiene on a local social media page.

Other bits of information need to come from data, for example the number of people tested in an area and how many were positive, or the number of contacts traced and whether there is a difference between demographic groups.

Local places are struggling to get access to this data, but it does exist.

The national government has set up national programmes like the Covid-19 data store, NHS Test + Trace, the NHS symptom tracking service and Project OASIS – which brings together data from various symptom tracking apps. As an aside this seems to be an exceptionally English approach, most other nations of a similar size seem to have built on existing regional and local structures.

All of these national programmes use data, for example to improve operational performance, to inform national decision makers, to support medical researchers, and to inform national media debate.

But the data they collect and steward is not getting to local places and those local places need it too.

It is not just me saying this

In public you can see regional Mayors, MPs, and Directors of Public Health complaining.

In private you hear the same and more.

Charities collecting and publishing data about social care because of government failure. Local academics being told that their research needs to conform with national health needs. Regions exploring whether to launch their own symptom tracking services. Businesses offering data services that may be of lower quality than that which the national government already holds. Local officials and community groups struggling to find out who to speak with to even start a conversation about data access.

In May there were reports that an interim operational review by a cross-government team highlighted the problem of data access. Tom Riodan, the CEO of Leeds Council, was given a role in the national Test + Trace programme after that review. His role is not only about data access but, as a result, some progress seems to be happening.

Despite this the national programmes still lack urgency and there are now concerns that the government will supply local places with dashboards that it and its national partners design, rather than giving local places access to data so that they can use it to design and operate whatever decision making tools they need. 

Meanwhile the public complaints will continue and the opportunity to make decisions that could save lives will be lost.

Accessing and using data in trustworthy ways

When data access is provided then it will need to be used in trustworthy ways.

Research by organisations like the Ada Lovelace Institute, UseMyData and Understanding Patient Data indicates that most people are more comfortable with data use if they see benefit for them and their communities. I hope local places have learnt lessons from the national government’s failures on transparency and excessive confidence in the capability of technology and data to solve complex problems to realise that even though they have the legal power and start with some trust that they need to to be transparent, engage with people who might be impacted, and be wary of harm.

Local public sector organisations have had the legal power to use personal health data since COPI (Control of Patient Information) notices were issued back on 1 April 2020. The notices were passed to support this kind of use.

Other organisations, such as charities or businesses, can use open data which is aggregated to a safe level.

For these organisations then daily publication of symptom, testing and contact tracing data at the level of LSOAs (Lower layer Super Output Areas) is likely to have the right balance between data protection and usefulness for public health. It is hard to be certain without access to the data. 

If the national programmes do not have the expertise to navigate these issues then they could get help from the Office of National Statistics who can both work through how to publish the data and help to communicate how this data for local operational decision making has different characteristics to statistical data.

The power of networks

When the data is available then it can start to rapidly be put to use.

Some local authorities are already working with their communities to prototype what they can do when, or if, the data arrives.

In other places there are networks ready to help.

ODI Leeds’ OpenDataSavesLives connects local authorities, health organisations, academia and businesses across the country. There are networks for specific groups of people like the Association of Directors of Public Health or Catalyst which helps charities. And networks for specific places like the Newcastle-based National Innovation Centre for Data’s DataJamNE, the LocalCoronavirusResponse team, or the network around the London Office for Tech and Innovation.

Networks like these can help get the data used in building tools for local places, evaluate the outcomes to discover what works and what does not, and share their learnings across the nation.

But they need the data

There are lessons to be learnt here, and not just about public health programmes in a pandemic.

If the UK wants to level up across the country it will need to do a lot more work on devolving data governance and learning how to get both local places and citizens represented in decision making about data. Perhaps the plan for the UK’s recovery after the pandemic or the national data strategy will tackle that particular challenge.

But there are also immediate steps that need to be taken.

We urgently need to get data out of these national programmes and to local places. It will help save lives.

Data institutions and implicit assumptions

I used to lead the Open Data Institute’s work on data institutions. The team both piloted data trusts and explained that a range of approaches existed – including things like data representatives and data cooperatives – that can change how decisions are made about data. Hopefully to make those decisions more trustworthy. There are many other people working on data institutions in the UK, in Europe and around the world. I’m often surprised by how many.

Over the last couple of weeks I have been talking with people about data institutions. Many of the conversations surface similar implicit assumptions.

There can be only one

In many of the conversations people assumed that there could be only one data institution within a particular context. They had not thought about whether and when there might be multiple.

Some data institutions will exist to steward data for which you might want there to only be a single source of truth1I know. I do love a bit of epistemology and discussions about the nature of ‘truth’ but that would be an unnecessary diversion in this blogpost – for example the list of Prime Ministers of a country, the list of websites that exist, or who you are married to.

Many others will steward data or have a purpose where there might be multiple things doing roughly similar jobs but, perhaps, with different methodologies or priorities. Maybe one has a purpose of “for the benefit of the people of Newcastle”, another has “for the economic benefit of the people of Newcastle” and a third has “for the benefit of the businesses of Newcastle”. A single word can make a big difference.

Sometimes there should be only one data institution but multiple will exist. That’s life. We live in a wonderfully imperfect world.

Being open to the need to work with other people and other institutions is a better starting assumption than there being only one. Institutions might compete with each other, cooperate with each other, or both, but do expect it to happen.

Rip it up and start again

Another assumption was about the need for something new.

The way we steward data at the moment is not working, therefore we must need a new institution to fix the problem, right? Maybe…

Sometimes we need to fix things that are not working, or at least try to make them better. An existing institution might provide vital services, it might contain valuable knowledge, or it might do things that – shock! horror! – are only loosely related to data. Creating a new institution might break existing and important things.

I do not know of a good methodology to help people decide when to try a revolution and when to try evolution, but do make sure that it is a conscious decision

You forgot government

Many people thought that they needed a new type of data institution – like a data trust or data cooperative – when actually they might just need to improve a simple, old-school democratic institution like a bit of government.

I am very conscious that I live in the UK, a high-income country with an old and (relatively…) stable democracy. Not everyone does. I’ve worked a lot internationally, but mostly in similar countries. In these countries we have many institutions that are already legally responsible and democratically accountable for stewarding data for a particular purpose.

There will be institutions responsible for land registries, local places, criminal justice systems, welfare payments and – in a country with a national health system like the UK – health and social care. Perhaps, rather than working around those government institutions you need to use democratic processes to change their behaviour to make them more useful and trustworthy. 

Some people seemed to forget the government and implicitly assumed that they needed to take responsibility into a new institution that they would build and run.

Sometimes we do need to take responsibility away from the government, but at other times we need to add new responsibilities to government or just make existing bits of government work a bit better.

Again, make it a conscious decision.

Building institutions takes time

Building institutions takes time. Not just your time, but other people’s too. It will take even longer if you do not think about why you are doing it and do not surface and challenge assumptions about what any new institutional arrangements should look like.

Assumptions like whether there will be multiple institutions, whether there should be something new, whether the institution should be part of the government, what approach you need, or even whether that approach is suitable for your particular context.

Making those assumptions explicit and challenging them is likely to help you move a bit faster and be a bit more effective at actually making people’s lives a bit better.

“Practical data ethics” talk at 2019 European Data Ethics Forum

Slides from talk

Hi, I’m Peter. I currently work at the ODI (Open Data Institute) where I am Director of Public Policy. I will start with my usual warning, particularly for an audience where English is not the first language. Sometimes I speak too quietly and too fast and I often make bad jokes and obscure references. I’m bad like that. This is my last public talk for the ODI so I am even more likely to do that than normal. Please tell me off if you cannot follow what I am saying. I will stop and get better.

About the ODI and about me


The ODI is a not-for-profit that works with businesses and governments to help build an open and trustworthy ecosystem. The ODI believes in a world where data works for everyone. As simple to describe, and as hard to achieve, as that.

In that world data improves the lives of every person, not necessarily every business or every government. Some businesses and governments are deliberately building new monopolies or causing harm to people. Sometimes it is not possible to fix that behaviour by working with organisations, instead it needs other ways to change behaviour. I will talk about those later.

At the ODI I have been heading up the public policy function — I’ve been responsible for the ODI’s views on the role of data in our societies.

I am a technologist by background and I somehow stumbled into the world of public policy a few years ago. One of the things I have been focussed on in that time is making sure that public policy is informed by and tested in practical research and delivery (and vice versa, that delivery work aligns with policy thinking). Data, technology and people are always changing. A strong link between practice and policy helps make stuff useful.

I am here to talk about practical data ethics. I would like to start by talking about how we create value from data; why we need to change the behaviour of people and organisations that collect, share and use data; and finally to talk about some possible interventions to change behaviour — including practical data ethics.

Creating value from data

Value is created from data when people make decisions.


To maximise the decisions that can be made we need to create tools that meet the needs of different decision makers — for example a mapping app to help me find the building that we are in today, a bit of sales and customer analysis to help a business decide whether to invest in a new product, or a research project to help a government decide whether and where to build a new road.

To create this range of tools we need to make data as open as possible.

This needs stewards — the people who decide who can get access to data — to make it accessible in ways that creators can use. There are a number of reasons why they might do this but it is (hopefully!) always driven by the need to use the data to tackle a problem by making a decision.

The problems with data

Unfortunately there has been a rush to collect data, open up data, share data, or make more decisions using data without thinking about whether or not we should.

Go, Gromit, go! https://www.youtube.com/watch?v=fwJHNw9jU_U

This is an ethics event so I am going to start by talking about harms. Rather than organisations making data work for people, they make it work against them.

Harm to individuals. People in the USA have been sent to prison based on decisions by a judge influenced by algorithms that could not be inspected or challenged. The algorithm was meant to reduce human mistakes and bias. Subsequent research has shown that the algorithm was “no more accurate or fair than predictions made by people with little or no criminal justice expertise”. It was probably less accurate than the person it replaced. It certainly wasn’t as accountable.

Harm to groups of people. These are often groups of people that are already disadvantaged.

The UK Government launched a new online service to check passport photos. It did this knowing that the service was more likely to fail to work for people with darker skin. To put it another way, the service was known to work better for white people than black people. Is that ethical? Should it be legal?

Meanwhile when the UK Government transferred the EU’s General Data Protection Regulation (GDPR) into UK legislation it put in place an exemption that reduce the protections in cases when government was using the data to enforce immigration controls. This follows the recent Windrush deportation scandal, which was partly built on unrealistic expectations of data availability and quality, and happened during the ongoing Brexit negotiations which could lead to 3 million EU citizens being at risk of deportation from the UK. A recent court case found that the data protection exemption was legal. But was it ethical?

Harm to groups of people is not always caused by personal data. The excellent book Group Privacy contains many examples. One that sticks in my head is from the South Sudanese Civil War. The Harvard Humanitarian Initiative published analysis created from satellite imagery to help people find and get aid to refugees. Unfortunately terrible human beings used the same analysis to find and attack those same refugees. The tools that the team had available had helped them think about mitigating the risk to individuals from the release of personal data, but not the threats to groups of people created by non-personal data.

And as a final example there has been damage to our democracies. The use of data in political advertising, to spread misinformation, or most famously in the Facebook/Cambridge Analytica debacle. Personally I do not think that the data collected by Cambridge Analytica had much effect, I reckon they sold snake oil, but the fear of it having had an effect is damage in and of itself.


Left unchecked these harms will lead us to a data wasteland where organisations do not collect or use data, people withdraw consent and give misleading data, and as a result we will get poor conclusions when we try to make decisions based on data. It reduces the social and economic value that data could create.

But there is another type of harm. Where people and organisations collect data but use it only for their own purposes. They don’t make data work for everyone. They just make it work for themselves.

This is data hoarding. It is the attitude that “data is oil and I must control it”. Data is collected and used within a single organisation for too narrow a purpose.

A simple example comes from Google. In recent years Google have encouraged people to crowdsource data about wheelchair accessibility in cities so that it is easier for people in wheelchairs to move around. But the data is only available in Google Maps. The people who contributed the data would surely have wanted it made more widely available so that people in wheelchairs who used Apple Maps could find their way around, or that the data was made available to civil society and city authorities who might have been able to use it to improve wheelchair accessibility in cities. Instead the data is hoarded by Google to create a competitive advantage and bring in more customers


There are vast amounts of data locked up in data monopolies like Google, Facebook, Apple, and legacy organisations like big multinational corporates or national mapping agencies.

This leads to lost opportunities for innovation. Innovation that might have created better outcomes for people. As a result lots of people are looking at data as a competition issue at the moment.

It also leads to lost opportunities for understanding and tackling major societal challenges like understanding the impact of the internet and web on our democracies, how to cope with aging populations or increasing urbanisation, or how to prevent or reduce the impact of climate change. We need to be careful of vital data infrastructure becoming over-reliant on the private sector firm, and the excessive data collection caused by some business models, but just imagine the data held by governments and businesses that could be made safely available to help with these problems.

The challenge is finding a path between the data wasteland and data hoarding. If we make data too open and available then it causes harm, if we do not make it open enough then we lose benefits and concentrate power in monopolies.


We need to move from a world where people are rushing to collect, share and use data to one where societies have more strategic decision making about data. Where data is as well maintained and useful as other forms of infrastructure like road, rail and energy. Where there is better legislation, rules, guidelines, and professionalism.

In doing that we need to recognise that different societies will make different decisions about data. Just like they make different decisions about other forms of infrastructure. People’s needs and social norms vary.

As long as we stay within democratic norms and respect fundamental human rights then we should accept those differences. Many of my examples today are from high-income countries but personally I am excited to see what new futures emerge from the rest of the world. That would be a different talk though.

Anyway, moving to a better data future will require constant monitoring and intervening by a range of people and organisations. The ODI is one of the organisations doing that monitoring and intervening. The strategy for how and when we do it is on the website.

Possible interventions

It is essential to think about the ecosystem around data and to think about multiple points of intervention. To create a world where data works for everyone many forms of intervention are needed. I am going to touch on some before getting to practical data ethics.

Many people start by thinking that better choices by citizens and consumers can change the world. Consumer power is the answer. Consumers will pick services from organisations that cause less harm and create more benefits.

Many people say that consumers are happy with the current situation — why else would they be using these organisations and services? Unfortunately work in the US by the academics Nora A Draper and Joseph Turow on digital resignation and the trade-off fallacy, and our own recent piece of work on how people in the UK feel about data about us, shows that most people do care and want a different future but that they feel unable to get there.

One of the things that is lacking is choice for consumers. The previously mentioned work on digital competition, and things like interoperability and data portability, will help but it will take time. It is not going to reduce some of the harms we can all see right now.

Regulators can intervene. In the UK the Open Banking movement designed a framework which was adopted by the UK’s banking regulator. It tackled competition issues, by giving bank customers more control over data about them, and had measures to protect against harms. Rather than open banking being solely down to consumer choice a regulator approves who bank customers can share data with. I helped a bit both with the framework and the persuasion to get it adopted. The process has taken at least four years and is just starting to see changes that benefit people.

Another necessary point of intervention is legislation. This is essential and can radically change the behaviour of businesses and governments. But again legislation takes time. That is a feature, not a bug, of democracy. Democracy comes with debate and compromise. GDPR took six years from the first legislative proposal until it came into force.


For more immediate change there is existing legislation that could be used — for example anti-discrimination legislation and worker’s rights — but that legislation is likely to need updating as, like any legislation, we will learn that there are gaps and changes to be made.

More recently people are proposing the creation of new institutions, like data cooperatives and data trusts, to create more collective power and collaborative decision making. I led a team doing both policy thinking and practical experimentation on these institutions. There are other people doing similar work in other countries.

But these new institutions are in a research and development stage. We have to be realistic that it will take more time to determine if they are useful, where they are useful, and how to build and regulate them.

Practical data ethics

There are many other possible points of intervention but one important and often overlooked one is the people within the organisations that collect, share and use data. Which brings me (finally!) to practical data ethics.

In the USA there have been growing protests by tech workers against the decisions made by their employers, in the UK research by DotEveryone found that “significant numbers of highly skilled people are voting with their feet and leaving jobs they feel could have negative consequences for people and society.” Meanwhile consumers and citizens are saying that they do care and do want more ethical technology, organisations respond to that. The need to retain both workers and customers creates a need to change.


We should never forget that, as my friend Ellen Broad put it in her book, decision are made by humans. Humans decide to fund or stop projects, to buy technology, they make design and development decisions, and they decide whether and how to evaluate its outcomes.

These decisions are influenced by consumers, governments and regulators but they are also influenced by other things such as professional codes, training courses and organisational methodologies.

Many people think the best way to intervene here is to define ethical principles. But, when we look out at the world we can see that many many principles have been created in the last few years yet are they having any impact? A recent study into the US Association for Computing Machinery’s code said no. Meanwhile, how will people know which principles to apply in a given organisation, sector, or country? Who gets to define the principles? What right do they have? Who holds people accountable to them?

This does not mean that principles are useless, within an organisation they can demonstrate values and help create space for challenge, but we need to look at other techniques to make them more useful at the systemic level where the ODI is looking to intervene.

When Ellen Broad and Amanda Smith looked at this for the ODI a few years ago. They came to the conclusion that the most useful thing for the ODI for to do was something a bit more practical and a bit more like the tools that people already use.

So, inspired by the business model canvas, we worked together to create a Data Ethics Canvas.


In the two years since then various other people — like Fiona, Anna and Caley — have worked with me to iterate it and helped turn it into to what you can see today. Not all of those people work for the ODI. We have been iterating it based on feedback from our own users and audience too.

The canvas does not give easy answers it ask questions. It encourages people to take responsibility for coming up with their own answers in their own contexts. The questions are inspired by the problems we and other see.

the black and white pictures are from the print-at-home canvas

It prompts people to think about their existing ethical and legislative context — perhaps they are already covered by health ethics or anti-discrimination legislation, or one of the many sets of AI and data ethics principles— and the limitations of data.

(By the way some principles, like those created by dataethics.eu, ask questions too)

The canvas prompts people to think of both possible positive and negative effects, but it encourages them to think more deeply about which groups of people win and lose.

The canvas is designed to be used by multi-disciplinary teams of people, not just individuals. We have seen it used by groups including lawyers, developers, programme managers, user researchers, policy analysts, designers and product managers. It encourages people in organisations to create space and time for debate, and then to make and act on decisions.

The canvas also encourages transparency and openness. That way people outside an organisation can see how it plans to use data, what benefits and risks are expected, and what mitigation plans are in place. It encourages people in organisations to listen to people who they might affect.

But is it having any effect?

I have used it in public training, private workshops and conversations with a range of organisations. I have seen it broaden people’s minds about the range of ethical issues that they should consider before making a decision. I have seen senior people in organisations try it in a few projects then go on to implement it in their standard project governance.

I have also seen individuals sneak it into a few projects within a large organisation with the goal of proving its value before talking more with their bosses. You normally don’t need permission to try a new methodology. Give it a go in your own organisations.

As well as providing paid training we openly publish a print-at-home version of the canvas and a detailed user guide on the ODI’s website so that anyone can use or remix it. The open licence on the canvas means that anyone has the ODI’s permission to do that.

It is hard to track usage of something that is openly published on the web but I know from our own research and surveys that hundreds of people in public, private and third sector organisations at local, national, and global levels are using it because of that decision to make it openly available.


Those people work in multiple sectors like academia, civil society, public service, health, finance, engineering. Some are in large corporates, some in small startups. People tell me that some organisations have stopped projects because of questions raised by the canvas. Others say that they have redesigned products and projects. Brilliant. It is causing some decisions to be made.

I can only share those stories vaguely, because I respect the confidence and privacy of those people.

One organisation, the UK Cooperative Group, have talked most about their use of the canvas. It forms part of their standard product development model. Because the canvas has an open licence they could adapt it to suit their own needs. Perfect. I hope some of the many, many others will share their stories too. I think it will be less scary than they might think.

I am always wary of over-confidence. At a place like the ODI we get listened to and the canvas could actually be making things worse. Is the effect overall positive and how big is it? Only time and more detailed evaluation will tell. But from my own checks I am reasonably confident that it is helping.


There are other people building similar tools that are useful in different contexts. I got my old team to use DotEveryone’s consequence scanning kit to look at data trusts — for that level of institutional change DotEveryone’s tool was a more useful approach. The team at the UK Digital Catapult have published a very useful paper categorising some of the tools that are available.

Obviously this approach to practical data ethics is only one type of intervention. Accountability — through organisational processes, professional codes, regulation and legislation is still very much needed. But practical data ethics can create some practical change now. If we can get people to be more open with their tales it should also inform policymakers on where the biggest problems are and what regulation and legislation is needed.


Building a better future for people with data will take quite a while. There are some obvious problems, some of which have obvious answers, but there also less obvious problems and no easy answers for all of the problems. We all have to keep monitoring and intervening at multiple points in the system.

We need to stay optimistic and believe that it is possible. I believe being optimistic is a political act that makes it more possible that we will build a world where data works for everyone.

Anyway, I have rambled on too long. It is time for less talking from stage and more talking with each other. Grab me if you want to chat or email me on peterkwells@gmail.com if you do not get a chance.

The data wasteland is polluted

Part of the ODI’s theory of change

At the Open Data Institute we use a theory of change. It is one of the tools that we use internally to help us make decisions and externally to explain to people what we do and how we do it.

Our theory of change describes the farmland, oilfield and wasteland futures and helps us try to steer between the extremes of the oilfield and wasteland futures to get to the farmland.

The wasteland future emerges when there are unaddressed fears arising from legitimate concerns — such as who has access to data and how it might be used.

We frequently talk through the theory of change to explain what we do and how we do it. We try to provide pauses in the conversation to get other people to give their opinions. It helps people to think and learn for themselves. It helps us learn too. We hear what other people think happens in the wasteland future. How they think people and organisations will react to their fears being unaddressed.

Most of us the people we talk with think that the wasteland future has a lack of data. They realise that with a lack of trust then many people and organisations will reduce how much data they share. They imagine people refusing to use services because they don’t trust them, and that organisations similarly refuse to share data because they fear being punished. They think the data stops flowing.

A smaller group of people realise the wasteland is more complex and weird. People’s behaviour will change in many different ways. Humans are fun like that.

Some people might post inaccurate data. Perhaps you will post fake claims of jogging exploits to social media if it is the only way to get a fair life insurance deal. Other people will hide in the data. Maybe we will give our children common names so they are hard to identify or so they appear to be from an ethnic group that is not discriminated against.

Similarly businesses will feel the need to create fake data. Organisations that fear that their supply chain data is being captured and used unfairly by their competitors might start to create ever more complex corporate structures to hide the data. Obviously reducing the chance of this unfair behaviour will also make it harder for regulators and civil society to know if a business is acting fairly.

I’m sure that even if you hadn’t thought of them at first you can now think of many more things that happen in the wasteland future.

You can see some of this future now. There are already people and organiastion hiding in the flows of data. Some of those people need and deserve help to hide because they have a genuine fear of harm, perhaps due to their political beliefs, ethnicity or sexuality. Equally there are others who are trying to evade fair scrutiny, for example tax dodgers and other criminals, and organisations providing services to help them do so. But if we increasingly fear harm then more people will want and need these services and, inevitably, they will become ever cheaper and used by more of us.

As this behaviour becomes widespread we will see data that is massively biased and misleading. People and organisations that use data-enabled services to tackle global challenges such as global warming, to price a life insurance premium in a way that doesn’t unfairly discriminate, or to decide whether or not to take a job will struggle. That would not be good for any of us.

Navigating the a route between the wasteland future and a different future where we get more economic and social value from data will not be easy. There will always be some people who need to pollute and hide in data to protect themselves from harm, we need to allow that to happen. Understanding and addressing people’s fears is not only a technical challenge, it is also a social and political one. To retain trust we need businesses and governments to adapt to people’s ever-changing expectations in a range of cultural contexts.

An increasing fear of how data is used will not simply stop people using services or sharing data, it will change peoples behaviour in a range of ways. If that happens we can expect data to be increasingly poor quality, biased and misleading. And that pollution will make data less useful to help people, communities and organisations make decisions that hold the potential to improve all of our lives. Some of that potential is false — the use of data required is too scary and people do not want or need it — but that is why it is important to understand and address the concerns we can if societies are to navigate towards the farmland.

You can read more about the ODI’s strategy and theory of change on our site.

The bumpy road to economic and social value

I moved to Newcastle in the North East of England last year. It’s a great place, but one of the things that first struck me about the town was the roads. There’s a motorway right through the town centre. It makes me think of tech and data, and the need to broaden the debate.

Roads for prosperity

Aerial view of the construction of the Central Motorway and Swan House roundabout, estimated to be in 1971. Image via The Evening Chronicle

When we were looking for a place to live we stopped in a few hotels near the town centre. They were on both sides of the motorway.

One side is full of shops, restaurants, cinemas, theatres and bars. The other is full of newly built university accomodation. There’s some rather strange, and a bit scary when it’s late and you’re tipsy…, skywalks connecting the two.

The motorway was opened in 1973 and was controversial at the time. Unsurprising when, as Professor Mark Tewdwr-Jones of Newcastle University says, “school playing fields and houses were…demolished”.

Glasgow motorways, courtesy of Google Maps and their various data suppliers

It was built following the Traffic in Towns report by Professor Sir Colin Douglas Buchanan. The report focussed on the growth in road traffic by cars, and the potential economic benefits that could be gained by supporting it.

Traffic in Towns was later followed by a 1989 government white paper, called The Roads for Prosperity, that followed the same tracks. Both reports gave a higher emphasis to inreasing road use and cars than to reducing environmental impact or other transport options, such as mass public transit or walking. They were design standards for urban transport. Their priority was economic growth.

Urban planners in other UK cities, like Birmingham and Glasgow, followed the same reports and the standards they set. Existing communities were again displaced or affected by roads that were built. A similar story happened in countries and cities across the world. Sometimes earlier, sometimes later.

New York City in the 1920s, Beijing in the 2000s

From the 1920s Robert Moses rebuilt New York City to favour car users as part of larger urban transformation plans. He constructed highways, bridges and parkways that cut through the city and surrounding regions to get cars to where they wanted to be. Debate over the impact of these decisions on communities, and whether Robert Moses’ politics and racism played a part in his decisions and the type of road uses he favoured, continues to this day.

Robert Moses had set the standard, other people followed his lead. Urban planners across the USA built roads that favoured road users and impacted on existing communities living in or near their path.

Beijing smog via a post by Marco Rinaldi

Many decades after Robert Moses, and as part of its preparation for the 2008 Olympics, Beijing refurbished 200 miles of roads and built two additional ring roads.

I was there in 2003 and remember standing in a hutong neighbourhood due for demolition. A resident showed me the straight lines on the map indicating where new roads were being built, and the lanes, streets and houses underneath that were either being demolished or left with greater air and noise population.

The potential benefits to be gained from the new roads had been decided to be greater than the current needs of the people who lived in Beijing. This wasn’t just about the Olympics. As part of the transition from the communist system under Mao Zedong to the market socialist / state capitalist society of current China there were similar infrastructure changes happening elsewhere across the country.

People push back

In each of these cases central authorities had decided that the potential economic gains outweighed the negative impact on people and communities without involving them in the process. People protested at the time but over the years the push back became more effective. It ended up changing the way we plan.

Anyone who followed the environmental protests in the UK in the 1990s will remember Swampy. (image copyright Reuters, I think).

In the UK there were growing protests against road developments during the 1980s and 1990s with calls for integrated transport solutions that considered different types of users like car, bus, rail, freight, bicycles and pedestrians and a reduced impact on the environment.

Gradually UK urban and road planning guidelines were changed to include the need for public consultation and the consideration of societal impacts like air quality, noise or other environmental issues. We now consider more viewpoints and needs before a decision is a made.

In parts of the USA change happened earlier. Jane Jacobs was one of the most famous figures amongst the groups in New York City arguing against Robert Moses’ plan to redevelop Greenwich Village in the 1950s and 1960s. She was part of the Joint Committee to Stop the Lower Manhattan Expressway, the ‘slum’ clearances it proposed and the decrease in air quality that it was forecast to generate. The Committee eventually won. Jane Jacobs started to formalise her thinking on urban planning in the book The Death and Life of Great American Cities. It argued for a new standard for urban design which shifted the emphasis towards the people who lived in the city.

A nail house in Hongkou, picture by Drew Bates. CC-BY-2.0.

In China, the most visible protests against the new roads and urban transformationm were ‘nail houses’, stubborn holdouts against the change. This became possible due to the strengthening of private ownership rights in the post-Communist era. In some cases the holdouts are people who don’t believe the public interest in this development outweighs their own interests, in others it will be speculative investors looking to profit from the public investment.

The parallels to tech and data

I work in the world of data policy at the Open Data Institute. We’re based in the UK but work globally.

I believe data, and large parts of what we call the technology or digital sector, are becoming infrastructure, just like roads became infrastructure in the past. This means that we need to think strategically and for the long-term. The effects of the decisions that we make today will persist.

A clip from one of the boss’s talks on the challenges of strengthening data infrastructure.

One of the things I’ve been doing over the last few years is reading about the history of technology-driven change. Things like the wireless, telephone, radio and roads. The web and internet have helped us communicate over a larger scale and at much faster speeds than previously, but we are still humans. We can learn from our history and the stages technology goes through as, or if…, it gets adopted. Perhaps by learning more historical lessons we can go through those stages faster and make better decisions than before.

An important of this process is how we moved from infrastructure decisions made solely by technocrats, whether in companies or in governments, to decisions being made with society and through our democratic processes. Unfortunately technology and data is currently stuck in the world of the technocrats with very little public involvement. We have more progress to make, otherwise the protests and bumps on the roads will get bigger.

We need to broaden the conversation, and open things up

We need to have broader conversations about technology.

This will be particularly important with data. Most data is about people, and multiple people at that. Our DNA reveals information about our parents, family and even our distant relatives. Utility bills reveal who we live with. Health records contain information about medical professionals as well as ourselves. Data is about us, our families, communities and society.

When we learn how to design services for multiple people then we will have to think about their different interests and rights & how they might compete with each other.

Yet, most internet services, and much current data regulation, are designed for individuals, particularly those who are currently online. That’s part of why technology can feel uncomfortable for many. It doesn’t match much of our societies. Rather than reflecting the richness and variety of communities and societies around the world tech is bringing in the political beliefs and cultural values of the people who built it.

As the French government showed with the Digital Republic Bill, and UK organisations like DotEveryone and the Carnegie Trust are exploring, engaging the public in decisions about technology is complicated but possible. We need more politicians and large technology companies around the world to embrace this approach.

We need to have broader and more open conversations that allow the public to both take part in and influence the outcomes of the current debates about technology. We need to go beyond technology experts to include a range of other experts and the people, businesses and communities who could be beneficially or negatively impacted by a decision. They will have different opinions, and different societies will choose to give those opinions different weights, but learning from the range of views and how they develop during a debate will help us make better decisions.

As societies learnt when we were building roads the debate can’t be left to technocrats solely focussed on economic gains, it needs to be opened up to the public so that we can also debate societal values.

You don’t control your Facebook posts, the reasons why are more complex than you might think

[facebook url=”https://www.facebook.com/FacebookUK/videos/1635229329867267/” /]

It told me that my “photos and posts” belong to me and that “[Facebook] won’t use them without [my] permission”.

The same advert has appeared in the feed of friends and work colleagues based in the UK. It seems to be part of a campaign. Perhaps the campaign is related to the imminent European Union’s General Data Protection Regulation and the growing public awareness that there is debate around data, how it is used, and whether to trust those uses.

There is a similar message in Facebook’s terms and conditions saying:

“You own all of the content and information you post on Facebook, and you can control how it is shared through your privacy and application settings”.

Both messages are simplistic, at best. I don’t fully own or control the content I post on Facebook. It doesn’t only belong to or affect me. By over-simplifying its messaging Facebook, like many other organisations, is missing the chance to help explain how its services work and help us all make better decisions when sharing content.

Social media content is more complex than you might think

This will sound counter-intuitive to many. I mean shouldn’t I have control over my data on Facebook? It’s about me! I created it!!

Don’t be silly. Data ‘ownership’ is not as straightforward as it sounds. Most of my content on Facebook is not only about me. It is about other people too.

These people are not my friends. They are from a film called Peter’s Friends. But it shows some people in a picture they may regret in later life.

My list of friends is a list of relationships with other people, people tag someone in a post saying that they went to a restaurant or pub with them, or share a picture or comment about a group of friends.

Most of us will think about our friend’s feelings when sharing content about them on social media, but we don’t always know what will be important to them. The rules aren’t written down. Many of us will have had the experience of sharing something and then having a friend say “hi, do you mind deleting that post because of X…”.

Sometimes we listen to those objections and sometimes we don’t. Our friends might not be able to delete our Facebook content without our consent but their views are part of the complex set of things we think about when posting. They can unfriend us in real-life as well as on social media.

Adverse impact on other people

Beyond affecting a personal relationship there are many types of adverse impact that a Facebook post might have. Affecting copyright owners is one. Copyright has many many flaws but it is one of the ways societies help creators benefit from their work.

A picture by a famous artist, Mr and Mrs Clark and Percy. Image used under fair use. Copyright David Hockney.

If I did own all the content I posted on Facebook then presumably I could post a picture created by someone else and start to make money off it by selling things. Money that could have gone to the artist.

I could, but I shouldn’t.

Both Facebook and I recognise that we need to abide by copyright legislation and that governments help enforce it. A copyright holder can complain directly to Facebook, or through the relevant national or international rules. The content is not mine to own to control and use how I wish. If I breach copyright in a way that unfairly impacts creators then fewer nice things get created. That would be bad.

Germany recently passed a new law stating that social media platforms have to take down hate speech within 1–7 days or face large fines.

Going deeper into adverse impact it could be that someone on Facebook posts something with the intent of causing harm.

To give just a few examples the content might libel someone, use hate speech, endorse terrorism, or use a sexual image of someone without their consent.

Facebook is a global service, and the legislation and definitions of those things will change from country to country, but in many countries those things would be illegal. A poster would lose control of the content, and perhaps even their liberty, as democratic governments use the powers given to them by people to stop the content from being seen and shared.

Facebook has its own moderation rules and tools that allow Facebook’s moderators to intervene proactively or for people to report content and get it removed. Again, that removal can happen without the poster’s consent. The poster is not in control.

Not all of the adverse impacts that moderation rules try to prevent are illegal and intentional. Others are unethical, or against social norms for a particular community or society. Moderation exists because the adverse impact from my posts might damage the health and goals of a community.

Both sassy socialist memes, with 1 millions followers, and sassy libertarian memes, with 200 followers, are real Facebook groups.

Moderation is not only done by Facebook and governments. Many community groups within Facebook have their own moderators and policies. Group moderators can also remove content without a poster’s consent.

Perhaps the moderators of sassy socialist memes or sassy libertarian memes will remove content I post in their groups if my content just ain’t sassy enough. The local Facebook group for the town I live in, like many other local Facebook groups, certainly has a fierce response to excessive advertising or outsiders criticising the town.

Other people can benefit from content

Shifting to a more positive, and less sassy, note people should also be aware of other people who can benefit from content they post. As the Financial Times recently noted “an explosion of [trustworthy data, such as that posted on Facebook] would give us the capability to understand our world in far more detail than ever before”. Facebook shares some of the data you post already so that other people can benefit, I think it should do more.

OpenStreetMap’s data is freely available as open data and used by governments, businesses, communities and indivudals all over the world.

For example, Facebook users help maintain data about things like cafes, restaurants and leisure centres. We don’t only need this type of data in Facebook, we need it in many other parts of our lives, so Facebook have been exploring how to share data with the community-maintained OpenStreetMap. That will help everyone using the thousands of services that use OpenStreetMap. The Facebook users are not in control of this flow of data but they, and many other people, will benefit.

In other sectors rather than downloading data I can give a third party that I trust the right to access it

In other contexts then Facebook users might want to share content that they post with a third party that they trust.

The EU’s General Data Protection Regulations strengthens this want to a right, although it is a right with limitations.

I might decide to do this so that it benefits my local community, for example helping local government understand feelings on a particular topic, to help deliver another service I want to receive, for example by asking my friends if they want to join me on a a new photo-sharing service, or to help me learn things about my own behaviour and habits.

Unfortunately despite Facebook telling me that I can control how data is shared I can’t easily share that data with third parties.

Facebook allows people to download data they post, but it is not in a standard format and I can’t simply give another organisation that I trust the right to access it to the same extent that, say, the UK banking sector is starting to do.

The UK’s banking sector is expecting to see increased competition and new services as a result of making it easier for people to share data. Perhaps social media firms and the people who use their services would benefit from a similar collaborative effort to determine how to safely share data, which mostly includes other people, without creating adverse impacts.

It is good that Facebook is starting to share data to create benefits outside of their own service. They should do more of it by sharing carefully anonymised data openly, more sensitive data in secure conditions with researchers working for the public good, and by giving people ways to safely share data that they post with third parties that they trust.

Explaining this stuff is hard, but it is necessary

This stuff is complex and can be hard to explain in an accessible way, but it is necessary to understand the complexity before trying to make it simple.

Like many other types of content and data, Facebook posts and photos can be about more than one person. The content can create adverse impacts for those other people but it can also create benefits too. Because of this, users are not fully in control of the content they post, and they certainly don’t own it in the same way that we might own a house or car. Instead civil society, governments and service providers need to work together to design ways to help give people more control and to maximise the social and economic benefits, while minimising the adverse impacts.

Over-simplifying this necessary complexity risks us slipping into a world where instead individuals fully control the data that they create. That is the world that Facebook’s ad is describing to many people. How silly. That world will reduce the benefits and increase the risk of harms.

We don’t need more lengthy and unreadable terms and conditions but as the debate over data grows it would be helpful if major service providers like Facebook took greater responsibility in helping to create a more informed debate and helping people to make better decisions.

A crap analogy

I was home recently and took my sister’s dog for a walk. When we were young we had dogs, Spud and Gyp, so it was a walk I’d taken before. A few things had changed. One was that there was less dog poo.

Me (left) taking my sister’s dog for a walk around Fairhaven Lake.

It was strange comparing the memories of those messy streets, including muck left behind by Spud, to the reality of the present day with dog walkers cleaning up and signs warning of penalties if they did not. There has been a change in our social norms. In return for the right to walk a dog, most people now accepted they needed to clear up behind them.

My day job is doing policy for the Open Data Institute. Policy is about changing outcomes, hopefully for the better.

On their own, legislation and guidance won’t fix challenges like data ethics, making data as openly available as possible, or the many other complex challenges that limit the social and economic value that societies get from data. It will need social change too.

I’m interested in how that change happens, including how society decided dog walkers should clean up the dunghills created by dogs.

People like having dogs, but dogs make a lot of shit

I found a blogpost about a book by Michael Brandow telling the tale of the introduction of a poop scooping law in New York City. I got a copy of the book and settled down for a read.

It would take a lot of rain to clean up 500,000 pounds of dog feces. (image Taxi Driver, copyright a big film company)

People like having dogs (*). They like having a companion. They like going for walks. Dogs can make people feel safer, particularly in a city that had as high a crime rate as 1970s New York. But dogs make a lot of shit (**).

In 1974 New York City’s Bureau of Animal Affairs estimated that 500,000 pounds of dog faeces were hitting the streets every day. The city’s population was growing. More people meant more dogs, more dog excrement and less space to step around it. That affected not just dog walkers but everyone else using the streets.

This sounded analogous to the interweb’s superhighways. While some people are having fun, other people are stepping in the dog doo-doo we make. I read on.

The dog doo-doo battle of many armies

There was a long battle to clean up New York City, it lasted for most of the 1970s. The battle involved many familiar armies.

There were a mix of civil society groups in the battle. Some wanted cleaner streets, others just wanted to keep walking their dogs, and some saw the opportunity for self-publicity. There were also people who didn’t care about the battle being waged under their feet.

A search on Amazon shows 1,357 results for ‘poop scoop’

There were businesses in the battle too. Some businesses simply wanted cleaner streets outside their shops. A pet food association objected to the final legislation because of the impact it might have on their customers, dog owners. Other businesses saw new opportunities. There was a boom in innovative, and probably disruptive, dirt cleaning solutions that continues to this day.

When dog owners look like their dogs is it correlation or causation? And which way is the causation? (source: National Library of Ireland on the commons)

Different government organisations took positions. In 1970 a new city Environmental Protection Agency had been created. Its leadership saw the opportunity to clear up a problem affecting citizens. Other organisations didn’t want the cost of enforcing new legislation and argued for others to take the lead.

Some organisations seemed to see a chance to pass part of the cost, and blame, for cleaning the streets to dog walkers. I suspect many other government organisations were wondering why all this effort was being spent on canine coprolites.

Meanwhile politicians were trying to navigate between all of these interest groups to tackle both this problem and others facing the city.

Politicians talking crap

Throughout the 1970s some argued that people could be persuaded to change behaviour without legislation through campaigns and leaflets. Both civil society groups and government organisations tried to do this and had some effect in parts of the city.

A waste receiver for dogs

Others said dogs should use bathrooms in houses, use different sides of the street on alternate days, or even be banned from the streets altogether. The mess caused by dogs risked all the enjoyment being taken away.

Some dog walkers, government organisations and politicians said that it was government’s job to scoop the poop and that government should have more resources for street cleaning.

There were politicians who thought that no legislation was needed as other problems took a higher priority. One politician said that he was keen for the legislation to happen as it would encourage city staff to focus on dogs rather than car parking fines. All politicians were heavily lobbied, by dog lovers and dog poo haters.

I can see a common pattern here. Regardless of whether the policy is about data or doo-doo we need public debate to gather ideas and decide who has to do what, what resources they have to do it with, and whether they get paid for the doing.

There was a campaign over public health issues with statements that an illness called toxocariasis, which can be caused by worms in dog excrement, was causing loss of eyesight in children. This risk appears to have been significantly overstated, although it looks like incidents of toxocariasis are reducing in the UK since dog waste laws were introduced there, but it was an effective campaign.

The debate raged until Ed Koch became Mayor and took a different tack. Rather than having another go at getting a new law passed in New York City’s legislature, he took the problem to the politicians at the New York State Senate. At the state level politicians debated how different solutions are needed in cities to more rural areas and passed legislation that only affected large cities (***). The law gave the city the power to fine people who didn’t scoop their pooch’s poop.

In all policy work sometimes you have to explore a few paths before you get to your goal.

Clearing up dog shit is good for society

Throughout the debate there was a common thread. A city that welcomed dogs but that had less dog faeces scattered around would be a better city.

Dog owners enjoyed the company of their dogs, but other people in their local communities were affected by their enjoyment. Pavements, or sidewalks in NYC, are shared spaces. Use and misuse of that shared space affects everyone who lives in the city. After a debate dog owners were prepared to take on the task of clearing up some of their mess for the benefit of wider society.

A super pooper scooper sign in North Vancouver communicating the new social norm in multiple languages. Image via “New York’s poop scoop law: dogs, the dirt and due process” by Michael Brandow

It is hard to know what was most effective — the debate, the civil society campaigns, the leaflets and signs, government loudly declaring that it had legislated, or the final push of fines. I’ve struggled to find good crap data. But the repeated legislative battles show us that NYC policymakers thought a law was required.

The book includes an interview saying that six years after the legislation was passed, 60% of dog owners were cooperating with the law. After a dog doo-doo battle which led to legislation for England and Wales in 1996, a larger shift in public behaviour was seen after more time had elapsed. A study in 2014 by three researchers from the University of Central Lancashire, 10 miles from my hometown, reported that only 3% of British people would not pick up their dog’s poo.

The shift from the streets and dog walkers of my childhood to one where only 3% of British people will not pick up dog poo is a significant change for the better (****). That is social change in action. Social change that made my walk a bit easier. Even though I now had to clear up after my sister’s dog everyone, including me, could enjoy the park a little bit more.

But, does this tale teach us how to make data better?

A crap analogy

Well, not directly. The title of this blogpost wasn’t a joke. It is a crap analogy. Our motives for using data are different from the simple motives — have fun, feel safe- of walking a dog. Data is not like doggy doodah.

While data is not like doggy doodah, Misha Rabinovich has shown that you can use data about faeces to make art. This artwork is temporarily installed at the Open Data Institute for a 2018 exhibition. I wonder if it subliminally got me thinking about this blogpost.

We can all agree what dog poo is, but we cannot all agree on the mess being created by how people are collecting, sharing and using data. We haven’t reached an agreement on what ‘good’ looks like and what outcome we are trying to achieve.

Meanwhile although the data ecosystem contains many of the same actors — individuals, civil society groups, businesses, and government organisations — each with their own changing motives and power it is more than a physical city. There are multiple virtual global villages which manifest themselves in our physical towns, cities, nations and continents. Someone in the UK can create mess on a virtual street used by people in Uruguay, the Ukraine and Uganda. It is trickier to deliberately change social norms and create better outcomes in such a complex system.

But the tale should remind us that given time and effort people are willing to change behaviour and reduce the negative impacts they have on other people. Do you need a New Year’s resolution for 2018? Let’s keep having fun with data, but let’s think more about other people and clean up some of the shit that we’re creating.

(*) and other pets, such as cats, that also lead to interesting tales about data

(**) data about other swear words is available

(***) UK politicians and dog waste policymakers would possibly benefit from reading that 1978 New York State Senate debate as it seems that UK is still discovering that while bagging it and binning it works in cities, in more rural areas you need to stick it and flick it.

(****) despite the improvements some people want city streets that are completely clean of the odious dog ordure. You will regularly see news articles about towns and cities saying that they might use CCTV tracking, registration schemes, and dog DNA databases to catch offenders. A company called MrDogPoop claims to have “the most powerful Dog Poop DNA matching database in the world” to help track down poops that avoid the scoop. These city-wide schemes tend to disappear when people realise the cost and debate uncovers that a rover registration scheme is too much of a stretch to our social norms.

Data and policy talk — November 2017

Approximate words of the talk I gave at the Data gedreven Beleidsontwikkeling / Data Congress event in November 2017.

Hi, I’m from the Open Data Institute, or ODI.

I’ve been asked to do a talk about “data and policy”. First, an apology. I don’t speak Dutch and sometimes I speak English too fast, and sometimes too quietly. That makes it harder for people who don’t speak English as a first language. Sorry. Shout at me if I do that and I’ll speak more clearly.

I want to start by expanding on the word policy. It means different things in different contexts.

Merriam-Webster has a definition of policy that says “a high-level overall plan embracing the general goals and acceptable procedures especially of a governmental body”.

That is a classic definition but there are other meanings and contexts.

Within organisations there will be policies for compliance with data regulation, like GDPR, or for how data should be collected, used, stored, shared or opened. Businesses, civil society and not-for-profit organisations will also have public policy positions on “government policies that affect the whole population”.

At the Open Data Institute lots of members of the team deal with all of these meanings of policy in different contexts. Most of my work is on public policy, but I’m trying to influence both governments and businesses.

The ODI is not-for-profit. We work globally, our headquarters are in the UK. We were founded by Sir Tim Berners-Lee, the inventor of the web, and Sir Nigel Shadbolt, an AI pioneer. We are not partisan but we are political. Data is a political topic. Open is a political statement. Our mission is knowledge for everyone.

A (hopefully) comprehensive map of where ODI has done work, where nodes have formed and where members are.

It’s our 5th birthday this year. Yay us 🙂 I’m going to share some policy lessons from those 5 years. The lessons have been learned from our work around the globe, our peer network of nodes and our network of members.

Policy is one of the capabilities we use to help us deliver our mission and strategy. We also do a lot of work with technology, training people, gathering evidence, building communities and incubating startups.

First, let’s talk about open data. Open data is vital and incredibly important but we learnt that if we only talk about and use open data then we can’t deliver our mission. Instead we work across the data spectrum.

the data spectrum

The data spectrum is about access. Who can get to data so they can use it or share it or etcetera. Some data should be kept closed within an organisation, like sales reports. Other data should be shared: the police need to be able to see your driving licence, medical records can help with research, twitter data can help us understand how social media is impacting our societies. Lots of data should be open data, things like bus timetables, maps and addresses.

At the ODI we learnt that we need to talk about and use the full spectrum of data to both get more open data and deliver on our mission.

We also learnt that we need to combat the very strange view that data is oil or coal or other types of fossil fuels.

I can, and often do, talk in economic theory about the different qualities of data and oil, but there is a more important difference. It creates the wrong mentality. People fight over control of oil. They want to hoard it for themselves. They want to sell it for huge amounts of money. This is not the way to get the most value from data, an increasingly abundant resource. The thinking generated by treating data like oil reduces innovative use of data and causes loss of trust by societies in how data is used.


Instead we need to turn data into infrastructure. It is already heading in that direction but we need to strengthen that momentum. Great infrastructure is boring, reliable, safe and easy to use. It’s there when we need it. Data is decades away from being boring, trust me *pause for ironic, self-knowing laughter*, but that’s the direction to head in. Turning data from every part of society — especially the public and private sectors – into safe, trusted and easy to use infrastructure that underpins every sector of our economy and our societies.

And that infrastructure will be built on a foundation of datasets that are made available as open data, for anyone to access, use and share. That foundation of open data makes it easier to publish and use other data.

The third lesson is about goals. Sometimes it can feel to other people like the goal of the open data movement is only to publish more open data or to put data on portals. That’s the wrong goal.


We think, talk about and use open data as a tool. One of several tools in the toolbox.

A toolbox that we, and others, use to tackle problems. Like finding a job that you enjoy, combatting corruption, finding your way around a city, responding to the threat of anti-microbial resistance, helping with house planning and building, or understanding the growth of new sectors and business models like the sharing economy (something we’re looking at in our new R&D programme).

The fourth lesson is about chance. Chance is great. Very unexpected things happen when you open up data. One of my personal favourites is that the UK government opened up radar data that was originally gathered for planning flood defences and people used it to discover both new places to grow wineand new Roman roads that criss-cross parts of the country. Fantastic. But that doesn’t always work.


Instead we learnt that we need to put more focus on creating impact by design. Looking for problems, working with people who are experts in tackling it and helping them to use data as one of the tools in their toolbox. When we do that then chance can also happen, but we also have a much higher chance of impact, and impact is necessary for sustainable change.

So those lessons are some of the ways we learnt to think about data over the last 5 years — about the full spectrum of data, about data as a tool, about impact by design, and about data as infrastructure. Those mental models are part of our approach to public policy.

But through our work and delivery we have also learnt some of the most effective levers that we have to create impact. In our policy work we amplify those levers and encourage others to use them or build their own.

First, practical advocacy.

Over the years we’ve developed a set of guides and a toolbox. They’re openly licenced. Anyone can use them, or fork them and change them. That can be a challenge for an organisation that needs to bring in revenues but it’s the right thing to do for a mission with an an open culture and a big mission. We don’t want to do everything, even if tried we wouldn’t be able to. We want to make it possible for other people to do what we do.


The practical advocacy tools keep on expanding.

We recently launched the first version of a data ethics canvas to help organisations using data understand, openly debate and decide on ethical issues about collecting, sharing and using data. Interestingly when we looked into data ethics we found that most of the debate was about personal data in the closed and shared parts of the data spectrum. People had missed the ethical issues around open data and non-personal data. The canvas might help fix that.


As part of our research & development programme we’re exploring how open data is being used in public sector service delivery and how it could be used more. There are some famous stories about open data helping to reimagine public services but we are still seeing the same old stories and not enough momentum. We’re hoping that through our research we can help understand the barriers to change, and build some methods and patterns that will help people do more things to use data to improve public services.

Patterns are important. We’ve also developed a set of design patterns for policymakers that use data to help them create impact. While data policy people might know data, many other policymakers don’t. We need to reach them and put data into their context, in language they understand and helping them understand how it can help them tackle their problems.


Through approaches like evidence-based policy many policymakers have realised that data can help inform policy, but these patterns also help show policymakers how data can help deliver policy. Whether that policy is reducing costs, improving an uncompetitive market, or helping consumers switch between service providers.

The next big lever is networks, peer networks in particular.

Peer networks are horizontal organisational structures with members who share similar identities, circumstances or contexts. We run global, African and European peer networks for open data and have seen their power in developing learnings and creating change. We’re learnt from how they have grown and how the people in them interact.


We’ve been seeing peer networks start to emerge in other work they do. Things like ODINE (open data incubator Europe), Datapitch (another Europe-wide startup incubator), and the sector programmes.

We believe that fostering other peer networks: in sectors, in particular disciplines (like policy), or in particular geographies will help build a better future faster. We’ve published a method report that we, or others, can use to do that.

Finally, sector programmes. We’ve been working with whole sectors to help them work together to use data. We can get more done if we work together.

Most people are familiar with organisations like the Open Government Partnership. Less well known are groups like GODAN (the Global Open Data for Agriculture & Nutrition) initiative that brings together governments, businesses and farmers to open up agriculture data to solve problems.


OpenActive is opening up sport data to make people more physically active. Places that offer a whole range of sports: football, squash, badminton, table tennis, running are opening up data and they’re also building an ecosystem of organisations that will use that data to make it easier for more people to play the sports they love.

In an initiative called open banking the UK retail banking sector is opening up data about products, locations and cash machines and creating open APIs so that people can choose to share data held about them by banks with people that they trust. We hope it will make it easier for more people to create better services for bank customers. It could also improve national statistics, help improve the UK’s identity framework, help tackle financial inclusion or many other things. We’re talking to other countries on multiple continents about helping them implement open banking too.

There are more sectors, like transport, coming together as they start to see the power of working together to solve common problems. We need to encourage sectors to understand and unlock the value of open data by focussing on infrastructure, skills and open innovation.


Finally, we’re launching a report today on the grocery retail sector and GDPR based on consumer research, sector interviews and our thinking about sectors. We want to encourage the retail sector to work together to focus on opportunities, and to use the data they hold in ways that both builds trust in shoppers and gives them better services.


But there’s an important point to understand with all of these levers. We are not building a new product or smartphone game. We are changing systems. This takes time. We are only a few decades into a large wave of technology driven change that will take many more decades to see through to the end.

Take geospatial data. People have been campaigning for open UK geospatial data for decades. Just last week there was another major commitment, a new Geospatial Commission and £80m of new government funding to maximise the value created by location data starting by opening up the UK government’s most detailed maps. It will take a few more years before the impact of that committment is fully seen.


And that’s why there’s another vital lesson. Having fun. Being optimistic. Sometimes it can feel like things are moving slowly or in a bad direction and that things will never get better. But just as open is a political statement, so optimism is a political act. Having fun helps me be optimistic. Choosing to be optimistic both helps the day go faster and creates the momentum we need to help create a better future.

Thank you.

Open data and advocacy — EU datathon

Approximate words of the talk I gave at the EU datathon in November 2017.

Hi, I’m from the Open Data Institute, or ODI. I’ve been asked to do a quick talk before the next panel about “open data and advocacy”. I’ll keep it quick so you can get to the panel and the Q&A. Asking questions is much more fun than listening to a presentation 🙂

We’re a not-for-profit. We work globally, our headquarters are in the UK. We were founded 5 years ago by Sir Tim Berners-Lee, the inventor of the web, and Sir Nigel Shadbolt, an AI pioneer. Our mission is knowledge for everyone.

As you might have seen on the first slide it’s our 5th birthday this year. Yay us. So, I want to share a bit about what we’ve learned about advocacy and open data in that time.

First, let’s talk about open data. Open data is vital and incredibly important but if we only talk about and use open data then we can’t deliver our mission. Instead we work across the data spectrum.

the data spectrum

The data spectrum is about access. Who can get to data so they can use it or share it or etcetera. Some data should be kept closed within an organisation, like sales reports. Other data should be shared: the police need to be able to see your driving licence, medical records can help with research, twitter data can help us understand how social media is impacting our societies. Lots of data should be open like bus timetables, maps and addresses.

We need to talk about and use the full spectrum of data if we were to get more open data made available so that anyone can access, use and share it.

The second lesson is about goals. Sometimes it can feel to other people like the goal of the open data movement is only to publish more open data or to put data on portals. That’s the wrong goal.


We think, talk about and use open data as a tool.

A tool that we use to solve problems. Like finding a job that you enjoy, combatting corruption, finding your way around a city, responding to the threat of anti-microbial resistance, helping with house planning and building, or understanding the growth of new sectors and business models like the sharing economy (something we’re looking at in our new R&D programme).

The third lesson is about chance. Chance is great. Very unexpected things happen when you open up data. One of my personal favourites is that the UK government opened up radar data that was originally gathered for planning flood defences and people used it to discover both new places to grow wine and new Roman roads that criss-cross parts of the country. Fantastic. But that doesn’t always work.


We need more focus on creating impact by design. Looking for problems, working with people who are experts in tackling it and getting them the data they need. To move data to the right place on the spectrum. When we do that then chance can also happen, but we also have a much higher chance of impact.

We also learnt that we need to combat the very strange view that data is oil or coal or other types of fossil fuels. I can talk in economic theory about the different qualities of data and oil, but there’s a more important difference. It creates the wrong mentality. People fight over control of oil. They want to hoard it for themselves. They want to sell it for huge amounts of money.


Instead we need to turn data into infrastructure. It is already heading in that direction but we need to strengthen that momentum. Great infrastructure is boring, reliable and safe to use. It’s there when we need it. Data is decades away from being boring, trust me *pause for ironic, self-knowing laughter*, but that’s the direction to head in. Turning data from the public and private sectors into infrastructure that underpins every sector of our economy and societies.

And that infrastructure will be built on a foundation of datasets that are made available as open data, for anyone to access, use and share. That foundation of open data makes it easier to publish and use other data. It’s a powerful way of thinking.

So those lessons are some of the ways we learnt to think — about the full spectrum of data, about data as a tool, about impact by design, and about data as infrastructure. Those mental models have helped our advocacy.

But over the last five years we have also learnt some methods that work to create impact.

We’ve been working with whole sectors to help them use data.

The UK retail banking sector is opening up data about products, locations and cash machines and creating open APIs so that people can choose to share data held about them by banks with people that they trust. We hope it will make it easier for more people to create better services for bank customers. We’re talking to other countries on multiple continents about helping them to make the same change. GODAN (the Global Open Data for Agriculture & Nutrition) initiative that we work with is working globally to open agriculture data to solve problems.


OpenActive is opening up sport data to make people more physically active. Places that offer a whole range of sports: football, squash, badminton, table tennis, running are opening up data and they’re also building an ecosystem of organisations that will use that data to make it easier for more people to play the sports they love.

There are more sectors, like transport, coming together as they start to see the power of working together to solve common problems. We need to encourage sectors to understand and unlock the value of open data by focussing on infrastructure, skills and open innovation.

We’re launching a report next week on the grocery retail sector and GDPR based on consumer research, sector interviews and our thinking about sectors. We want to encourage the retail sector to work together to focus on opportunities, and to use the data they hold in ways that builds trust in shoppers and gives them better services.


As well as sector programmes we work on practical advocacy. Here’s two examples.

  • A set of design patterns for policymakers that use data to help them create impact. While data policy people know data, many other policymakers don’t. We need to reach them and put data into their context, in language they understand and tackling problems they need to solve.
  • A data ethics canvas to help organisations using data understand, openly debate and decide on ethical issues about collecting, sharing and using data. Interestingly when we looked at data ethics we found that most of the debate was about personal data in the closed and shared parts of the data spectrum. People had missed the ethical issues around open data.

We’ve also been working on networks. Peer networks are horizontal organisational structures with members who share similar identities, circumstances or contexts. We run global, African and European peer networks for open data and have seen their power in developing learnings and creating change. We’re learnt from how they have grown and how the people in them interact.


We’ve been seeing peer networks start to emerge in other work they do. Things like ODINE (open data incubator Europe), Datapitch (another Europe-wide startup incubator), and the sector programmes.

We believe that fostering other peer networks: in sectors, in particular disciplines (like policy), or in particular geographies will help build a better future faster. We’ve published a method report that we, or others, can use to do that.


Oh and finally, there’s another vital method. Having fun. Sometimes it can feel like things are moving slowly or in a bad direction and that things will never get better. But just as open is a political statement, we should also be aware that optimism is a political act. Having fun helps me be optimistic. Choosing to be optimistic both helps the day go faster and helps create a better future.

Thank you. I hope this talk and the rest of the event is both fun and useful.

Learning from historical waves

As I’ve been starting to get to grips with technology policy over the last few years one of the things that has fascinated me is how little reference to history there is. When I read historical books and talk to people about technology and innovation history I find some frequent gaps. We need to learn from history if we are to make the best of the opportunity created by the current waves of innovation and technology.

Whatsapp and Columbus

The Landing of Columbus by John Vanderlyn

For example, people talking about the wonders of technology talk about how few staff WhatsApp had when they were bought by Facebook, yet don’t talk about how few people sailed in the Niña, the Pinta, and the Santa Maria when Columbus sailed across the Atlantic. After Columbus’ expedition more and more people crossed the Atlantic, for exploration, for business and for pleasure.

WhatsApp’s success built on the internet, the web, cryptography and smartphones. Similarly Columbus relied on inventions in navigation and shipbuilding. Neither could have achieved what they did without those previous inventions. Are they analogous?

Learning lessons from history

Recently I read a couple of books that helped me sort out some of my thinking about lessons from previous waves of technology-driven change. The books were Ruling The Waves by Deborah L. Spar and The Master Switch by Tim Wu. They are good books. If you’re interested in technology policy you should read them too. I’ll lend you my copies if you want.

Ruling The Waves uses ocean sailing, telegraph, radio, satellite television, cryptography, personal computer operating systems and digital music to explore innovation. It proposes that they show four common phases: innovation, commercialisation, creative anarchy and rules. Different actors dominate in each those phases.

There are piratical adventures in the early years before the surviving, and now dominant, winners encourage government to work with them to bring order to the new technology. Using the model of this book would show that my silly Whatsapp/Columbus analogy is fatally flawed. Columbus was in the innovation phase, Whatsapp (and other messaging services) are in either the creative anarchy or rules phase. They’re very different kinds of innovators.

Ruling the Waves argues that the eventual rules tend to be dominated by intellectual and property rights. It shows that it can take decades, or even centuries, from innovation until stable rules are in place.

The Master Switch uses the Greek myth of the titan Kronos devouring his children as an analogy for existing monopolies devouring startups. This is Goya’s verion of that myth, using the titan’s Roman name of Saturn.

The Master Switch looks at lessons from the telephone, radio, broadcast and cable television, and Apple to propose that all information technologies go through a cycle of decentralisation to centralisation ending with a corporate (or state) monopoly where innovation, the economy and consumers suffer.

It argues that a separation principle can help prevent this fate.

This principle would keep a distance between young industries and existing monopolies to enable new technologies to show their worth; between different markets to make it harder for monopolies to spread; and between the public and private sectors to prevent government from favouring friendly monopolies.

After reading the books I was more convinced than ever that the waves of change bought about by the internet and web will take decades, if not centuries, to be absorbed into our societies. It is seductive but false to think that we can legislate for technology and data quickly. We have to allow for experiments to learn the right legislative and regulatory frameworks.

Gaps in the lessons

But there were gaps in the books. That’s not unique. I see the same gaps in lots of technology policy and thinking.

Despite the best efforts of Victorian inventors the vast majority of dinner tables do not yet feature a minature railway delivering food to bearded men. Picture from Victorian Inventions by Leonard de Vries

Major enabling waves of technology like the internet and web underpin lots of other innovation — like smartphones, social media and search engines—that each have their own journeys to go through. Some of these smaller waves will have lasting impact, some may disappear and get washed away, others are badly timed and will come back in a while. But the waves don’t stop. They are continuous. That is one of the reasons why open culture is so important. It keeps us open to innovation, new ideas and challenges from outside of a small circle of friends and organisations.

Both books miss the impact of data in the current period of change and that much of this data is personal data. It is data about you, me and billions of other people. Most data is about interactions between people, or between people and organisations staffed by other people. It is difficult, if not impossible, to determine who ‘owns’ data. For most data there will be multiple people and organisations who have rights. This makes it hard to rely on property rights as a way to shape and bring rules to the market. The challenge of building good governance for data infrastructure will need a more systemic response than property rights.

There’s a whole world of innovation out there. (Gall-Peters projection, image by Strebe CC-BY-SA 3.0)

The books also focus on the US and UK, with some excursions into mainland Europe. While they describe the differences between European and US approaches to regulation, with Europe typically intervening more, I would love to see more about the lessons learned by other countries. The web, the internet and data infrastructure cross, and therefore soften, national boundaries. Learning from and listening to other countries and societies will become even more important as these waves of technology reach their full power. These excellent recent reports from the Web Foundation are useful for those in a US/UK filter bubble who want to start listening more widely.

Innovation has limits

And finally both books miss the influence of societies and people. They are books about economy, regulation and business. They miss the social side of the change.

Lots of the impact of technology is societal as well as economic. Similarly the forces that impact on and affect technology change are both societal and economic. People adapt to technology and innovation, but sometimes they push back and reject it. Those rejections can be learned from.

The innovations that led to Christopher Columbus crossing the Atlantic also led to industrialised slavery. Slavery might have helped create the modern world but it is an evil that should not have happened and should not still be happening. We could have intervened earlier and stronger to stop it. A modern world similar, but not the same as, our current one would still have been built. It would have taken longer but it would have damaged billions fewer people in the process. Our societal norms now reject slavery and many of the other things that that particular innovation enabled.

As our societies matured we embedded some of those societal norms and values into legislation. Human rights, worker’s rights, anti-discrimination, health and safety, and data protection are some obvious examples. They are strong signals from society indicating where innovation is encouraged and where it isn’t.

The precise rules will vary by country but while the boundaries of legislation will contain things that need to adapt as we learn how to do things better at the core of the legislation are societal norms and values. We cannot and should not forget our values as we go through this wave of change. Those values do change but that change should be vigorously and openly debated.

Something the team at the ODI say a lot.

Innovation can take strange paths and be used for unintended purposes. We need to engage and work openly with societies and people if we are to both understand the limits and share the benefits of the current waves of technology.

What does this have to do with my job?

Over the last couple of years I’ve been working at the Open Data Institute where I spend about 50% of my time working with the private and public sectors delivering projects and building services. We help businesses and governments understand and adapt to the wave of change being bought about by data. The other 50% of my time is spent developing our policy thinking based on what I and the rest of the team and network learnt from delivery and research.

In that second half of my time one of the many things I’ve been helping on is developing a line of thinking that data is becoming a new form of infrastructure. That a data infrastructure which is as open as possible is one that will create the most impact and be best for people, businesses, societies and the planet and that we need to build an open future for data.

Clearly data is not “good” infrastructure right now, too many people can’t get the data that they need, so we think a lot about how governments and businesses can help strengthen it. We look at history when we do that. This is all part of my research. How did we recognise things becoming infrastructure in the past? How did we learn how to design and build good infrastructure? How long did it take? Do historical examples contain useful lessons?

What should I read next?

Anyway, like all of my blogs, I’m thinking out loud. These are some of the things my recent work and reading about history has made me think about. The gaps in the last two books led me to pick a book on the anthropology of roads as my next one. What should I read or who should I talk to after that?

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