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.
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 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.