Complexity and complementarity – why more raw material alone won’t necessarily bring open data driven growth

[Summary: reflections on an open data hack day, complexity, and complements to open data for economic and social impact. Cross posted from Open Data Impacts blog.]

“Data is the raw material of the 21st Century”.

It’s a claim that has been made in various forms by former US CIO Vivek Kundra (PDF), by large consultancies and tech commentators, and that is regularly repeated in speeches by UK Cabinet Office Minister Francis Maude, mostly in relation to the drive to open up government data. This raw material, it is hoped, will bring about new forms of economic activity and growth. There is certainly evidence to suggest that for some forms of government data, particularly ‘infrastructural’ data, moving to free and open access can stimulate economic activity. But, for many open data advocates, the evidence is not showing the sorts of returns on investment, or even the ‘gold rush’ of developers picking over data catalogues to exploit newly available data that they had expected.

At a hack-event held at the soon-to-be-launched Open Data Institute in London this week, a number of speakers highlighted the challenge of getting open data used: the portals are built, but the users do not necessarily come. Data quality, poor meta-data, inaccessible language, and the difficulty of finding wheat amongst the chaff of data were all diagnosed as part of the problem, with some interesting interfaces and tools developed to try and improve data description and discovery. Yet these diagnosis and solutions are still based on linear thinking: when a dataset is truly accessible, then it will be used, and economic benefits will flow.

Owen Barder identifies the same sort of linear thinking in much macro-economic international development policy of the 70s and 80s in his recent Development Drums podcast lecture on complexity and development. The lecture explores the question of how countries with similar levels of ‘raw materials’ in terms of human and physical capital, could have had such different growth rates over the last half century. The answer, it suggests, lies in the complexity of economic development – where we need not just raw materials, but diverse sets of skills and supply chains, frameworks, cultures and practices. Making the raw materials available is rarely enough for economic growth. And this something that open data advocates focussed on economic returns on data need to grapple with.

Thinking about open data use as part of a complex system involves paying attention to many different dimensions of the environment around data. Jose Alonso highlights “the political, legal, organisation, social, technical and economic” as all being important areas to focus on. One way of grounding notions of complexity in thinking about open data use, that I was introduced to in working on a paper with George Kuk last year, is through the concept of ‘complementarity’. Essentially A complements B if A and B together are more than the sum of their parts. For example, a mobile phone application and an app store are complements: as the software in one, needs the business model and delivery mechanisms in the other in order to be used.

The challenge then is to identify all the things that may complement open data for a particular use; or, more importantly, to identify all those processes already out there in the economy to which certain open data sets are a complement. Whilst the example above of complements appears at first glance technological (apps and app stores), behind it are economic, social and legal complementarities, amongst others. Investors, payment processing services, app store business models, remmitance to developers, and often-times, stable jobs for developers in an existing buoyant IT industry that allow them to either work on apps for fun in spare time, or to leave work with enough capital to take a risk on building their own applications are all part of the economic background. Developer meet-ups, online fora, clear licensing of data, no fear of state censorship of applications built and so-on contribute to the social and legal background. These parts of the complex landscape generally cannot be centrally planned or controlled, but equally they cannot be ignored when we are asking why the provision of a raw material has not brought about anticipated use.

As I start work on the ‘Exploring the Emerging Impacts of Open Data in the South‘ project with the Web Foundation and IDRC, understanding the possible complements of open data for economic, political and social use may provide one route to explore which countries and contexts are likely to see strong returns from open data policy, and to see what sorts of strategies states, donors and communities can adopt to increase their opportunity to gain potential benefits and avoid possible pitfalls of greater access to open data. Perhaps for further Open Data Institute hack days, it can also encourage more action to address the complex landscape in which open data sits, rather than just linear extensions of data platforms that exist in the hope that the users will eventually come*.

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