How do you take the same data that everybody has access to and convert it into a billion dollar business? When do you look at all the data in the world and say you want more (and that you are going to collect it like no one has done before)? How do you stop worrying about open data, and begin solving development challenges instead? Who is doing what with open data and how and why?
Our world is awash with increasing amounts of data, but potential audiences for this data remain under-served for the most obvious of reasons - the data just doesn’t speak their language.
This has been true for the data on the World Bank Group Finances website which has only ‘spoken’ English since it was launched. Yes, we should have done this earlier but the website, and its associated open datasets, are now available in 5 new additional languages - Chinese, French, Hindi, Russian, and Spanish . The mobile app has been available for some time in 9 languages (Arabic, Chinese, English, French, Hindi, Indonesian Bahasa, Portuguese, Russian, and Spanish) and the new release of the website is in line with the program’s quest to include new audiences and communities in the use and dissemination of open financial data.
The open data community is chock-full of do-gooders.
There are "open" data-driven applications that track government legislation in the US, tools that help calculate taxi fares in Bogota, Colombia, applications that track how tax payer funds are spent in the UK, the state of school sanitation in Nepal, and many more.
It's clear that innovators are out there and full of terrific ideas about how to help their fellow citizens by harnessing public data. The question is, how can more of these projects follow examples like GovTrack and transition from hobby to successful, sustainable business models? And while there may be technical talent out there, what about entrepreneurial skills? How many data rockstars out there also have the "courage to create a business"?
The final report from the Big Data for International Development DataDive came out a few days ago (see below) and the obvious question is what's next? Sure, the DataDive was a success in terms of the number and caliber of people that participated, the ambition and scope of the problems they worked on (mostly around better/faster/cheaper poverty measurement, and more effective/proactive fight against fraud and corruption), and the results that were achieved in a very short span of time (showing fairly conclusively that big data based approaches can be effectively applied in the context of international development). The report itself points out a few next steps (a data competition, specific action items against each project that the teams worked on, the need to embrace new types of data skills and techniques, and continued effort to open new and more diverse data from both private and public sources) but here is a look at some other themes that emerged during the dive that are probably also worth thinking about -
Image Credit: World Bank Flickr
Why worry about the demand for open data?
When it comes to open data, much has been done around what we can publish, but much more can be done on identifying what others might need and want. Many open data initiatives have been started as supply-driven efforts seeking to increase transparency and leverage new information dissemination technologies - and that’s been a good way to start. However, being supply-driven is not the only way forward – a genuinely demand-driven approach would allow data providers to respond to, rather than anticipate, the data needs of users.
So what is the demand for open data? This is a simple question that is difficult to answer. Unearthing even elements of the answer would help to increase understanding, inform the continued practical growth of open data efforts and activities, and hopefully result in more relevant, accessible, and widely-used data.
Photo Credit: Neil Fantom
A more detailed recap will follow soon but here’s a very quick hats off to the about 150 data scientists, civic hackers, visual analytics savants, poverty specialists, and fraud/anti-corruption experts that made the Big Data Exploration at Washington DC over the weekend such an eye-opener.
If you haven’t registered yet for the Big Data Exploration event at the World Bank on March 15-17, you really should. After stops in Venice, Vienna, and a pre-event at Washington DC, data divers assemble at DC this weekend to take another crack at issues related to poverty measurement, plus fraud/anti-corruption in operations and to demonstrate whether and how practitioners can use big/open data to get results for traditionally knotty development problems (which are relatively difficult or expensive to resolve using standard techniques).
If you're playing catch up, read more about the plans and potential impact for future Data Dives. Also have a look at what colleagues at a Data Dive in Venice accomplished by analysing World Bank contracts and vendors. And now, read the cross-posted blog below from UNDP's Giulio Quaggiotto and World Bank's Prasanna Lal Das who ask: Would You Give Up Your Personal Data for Development?
Let’s say you are in the middle of what others may call ‘nowhere’ and need information on the Bank’s work in the vicinity before an upcoming meeting with local officials. Or you are a civil society organization rep and want to make sure that the numbers you have about a particular project are the same as what the Bank reports (and if not, you want to know why not).
Your laptop is no good because - it is the middle of nowhere after all! - and you can only rue your decision to leave your stack of papers behind.
What do you do? Well, the answer might be in your pocket.
It took longer than we'd hoped but it's finally here - the new World Bank Finances app answers many of the questions you asked after the release of the first version last year (click here to download the new version for Android; an updated iOS version will be out soon).
In the World Bank Finances team, we're currently asking ourselves what's next after publishing open financial data? What comes after transparency?
There's of course a lot we still need to do -- we need to help other people publish data (other people's data can make ours even more powerful and help tell more complete stories), we need to help people learn to use our data, we need to raise awareness about the availability and potential of open data, there of course is more (and more granular) data we still need to publish, and the like.