Open data value creation in the digital economy

Whether you call it open day-ta or open dah-ta, the practice of releasing data sets into the public domain leaving its take-up to chance belies a not-for-profit mentality that may provide some value to the community but has little impact on the growth of the digital economy.

Information is data with context. End-users want information, not data, but the task of adding the context often falls to volunteer programmers who participate in weekend hackathons that are highly worthy but rarely produce any market ready products.

On one hand, a lot of creativity and know-how exists to develop smart applications based on open data sets. On the other hand, solid business models to bring these apps to the market and make them viable are often lacking.

Business is driven by supply and demand and companies usually try to identify their customers’ needs in advance so that they can match supply and demand more accurately. On the other hand the prevalent model in open data is one where Governments release the data into the public domain with no prior assessment of its viability. The criteria seems to be if it’s ready to go and it’s not producing a revenue stream, then release it. The releases often take place without an update plan, which is a common inhibitor to application development.

Compare this with McKinsey who in its article What Executives Should Know about Open Data suggests that $3 trillion or more in annual value could arise from the use of open data in applications across seven domains of the global economy - education, transportation, consumer products, electricity, oil and gas, healthcare and consumer finance.

This could be driven by data aggregators, who are assembling, rendering anonymous, and selling a wide range of data flows or by creating an eBay for data - a market place of companies trading data directly between themselves.

There’s something idealistic about Government open data initiatives that is reminiscent of the early days of social media. People want to encourage its release because the alternative is not to release it and people don’t want that. However conversion of open data sets to successful applications is relatively low because developers generally have to make do with prescribed data. Whether the best developers are attracted by this process is debatable.

There are ways in which open data can be made more viable. More public sector websites could allow people to request or vote for the release of a specific data set. Many Government organisations haven’t yet gone this far, neither do they realise that Freedom of Information requests may contain clues as to what types of data people want. It’s a good idea therefore to filter FOI requests with a view to prioritising open data sets. Going a step further, social media surveys and crowd sourcing techniques could be used to enable the public to choose from a selection of data sets.

I’d also like to see the concept of brokerage being introduced into open data. In this scenario, experts from the business world would help the government to identify and release the data sets that are most commercially viable or will have the most community benefit, match them with the right sponsors and developers and provide a feedback channel from the market as to what the quality of those data sets was like.

The public sector currently releases data sets on the basis that they are available to hand and can be released without cost. This won’t always be the case and preparing data sets for release will begin to cost money. On the other hand, managing and analysing data from internal and external sources will become essential if businesses are to remain competitive.

Open data brokers, data market places and data aggregators are among a new breed of players that can help both public and private sectors to get more from open data and increase its relevance in the digital economy.