Slow down with the standards talk: it’s interoperability & information quality we should focus on
[Summary: cross-posting a contribution to the discussions on the International Open Data Conference blog]
There is a lot of focus in the run up the International Open Data Conference in Ottawa next week. Two of the Action Area workshops on Friday are framed in terms of standards – at the level of data publication best practices, and collaboration between the standards projects working on thematic content standards at the global level.
It’s also a conversation of great relevance to local initiatives, with CTIC writing on the increasing tendancy of national open data regulations to focus on specific datasets that should be published, and to prescribe data standards to be used. This is trend mirrored in the UK Local Government Transparency code, accompanied by schema guidance from Local Government Association, and even where governments are not mandating standards, community efforts have emerged in the US and Australia to develop common schemas for publication of local data – covering topics from budgets to public toilet locations.
But – is all this work on standards heading in the right direction? In his inimitable style, Friedrich Lindenberg has offered a powerful provocation, challenging those working on standards to consider whether the lofty goal of creating common ways of describing the world so that all our tools just seamlessly work together is really a coherent or sensible one to be aiming for.
As Friedrich notes, there are many different meanings of the word ‘standard’, and often multiple versions of the word are in play in our discussions and our actions. Data standards like the the General Transit Feed Specification, International Aid Transparency Initiative Schema, or Open Contracting Data Standard are not just technical descriptions of how to publish data: they are also rhetorical and discplinary interventions, setting out priorities about what should be published, and how it should be represented. The long history of (failed) attempts to find general logical languages to describe the world across different contexts should tell us that data standards are always going to encode all sorts of social and cultural assumptions – and that the complexity of our real-world relationships, and all that we want to know about the different overalapping institutional domains that affect our lives will never be easily rendered into a single set of schema.
This is not to say we should not pursue standardisation: standards are an important tool. But I want to suggest that we should embed our talk of standards within a wider discussion about interoperability, and information quality.
An interop approach
I had the chance to take a few minutes out of IODC conference preparations last week to catch up with Urs Gaser, co-author of Interop: The Promise and Perils of Highly Interconnected Systems, and one of the leaders of the ongoing interop research effort. As Urs explained, an interoperability lens provides another way of thinking about the problem standards are working to address.
Where a focus on standards leads us to focus on getting all data represented in a common format, and on using technical specifications to pursue policy goals – an interoperability focus can allow us to incorporate a wider range of strategies: from allowing the presence of translation and brokering layers between different datasets, to focussing on policy problems directly to secure the collection and disclosure of important information.
And even more importantly, an interop approach allows us to discuss what the right level of interoperability to aim for is in any situation: recognising, for example, that as standards become embedded, and sunk into our information infrastructures, they can shift from being a platform for innovation, to a source of innertia and constraints on progress. Getting the interopabiliy level right in global standards is also important from a power perspective: too much interoperability can constrain the ability of countries and localities to adapt how they express data to meet their own needs.
For example, looked at through a standards lense, the existence of different data schema for describing the location of public toilets in Sydney, Chennai and London is a problem. From the standards perspective we want everyone to converge on the same schema and to use the same file formats. For that we’re going to need a committee to manage a global standard, and an in-depth process of enrolling people in the standard. And the result with almost undoubtedly be just one more standard out there, rather than one standard to rule them all, as the obligatory XKCD cartoon contends.
But through an interoperability lense, the first question is what level of interoperability do we really need? Andwhat are the consequences of the level we are striving for?. It invites us to think about the different users of data, and how interoperablity affects them. For example, a common data schema used by all cities might allow a firm providing a loo-location app in Ottawa to use the same technical framework in Chennai, but is this really the ideal outcome? But the consequences of this could be to crowd out local developers who could build something much more culturally contextualised. And there is generally nothing to stop the Ottawa firm from building a translation layer between the schemas used in their app, and the data disclosed in other cities – as long as the disclosure of data in each context include certain key elements, and are internally consistent.
Secondly, an interoperability lens encourages us to consider a whole range of strategies: from regulations that call consistent disclosure of certain information without going as far as giving schema, to programmes to develop common identification infrastructures, to the development and co-funding of tools that bridge between data captured in different countries and contexts, and the fostering of collaborations between organisations to work together on aggregating heterogenous data.
As conversations develop around how to enable collaboration between groups working on open aid data, public contracts, budgets, extractives and so-on, it is important to keep the full range of tools on the table for how we might enable users to find connections between data, and how the interoperability of different data sources might be secured: from building tools and platforms, working together on identifiers and small building-blocks of common infrastructure, to advocating for specific disclosure policies and, of course, discussing standards.
When it comes down to it – for many initiatives, standards and interoperability are only a means to another end. The International Aid Transparency Initiative cares about giving aid recieving governments a clear picture of the resources available to them. The Open Contracting Partnership want citizens to have the data they need to be more engaged in contracting, and for corruption in procurement to be identified and stopped. And the architects of public loo data standards don’t want you to get caught short.
Yet often our information quality goals can get lost as we focus on assessing and measuring the compliance of data with schema specs. Interoperability and quality are distinct concepts, although they are closely linked. Having standardised, or at least interoperable data, makes it easier to build tools which go some of the way to assessing information quality for example.
But assessing information quality goes beyond this. Assessments need to take place from the perspective of real use-cases. Whilst often standardisation aims at abstraction, our work on promoting the quality, relevance and utility of data sharing – at both the local and global levels – has to be rooted in very grounded problems and projects. Some of the work Johanna Walker and Mark Frank have started on user-centered methods for open data assessment, and Global Integrity’s bottom-up Follow The Money work starts us down this path, but we’ve much more work to do to make sure our discussions of data quality are substantive as well as technical.
Thinking about assessing information quality distinct from interoperability can also help us to critically analyse the interoperability ecosystems that are being developed. We can look at whether an interoperability approach is delivering information quality for a suitable diverse range of stakeholders, or whether the costs of getting information to the required quality for use are falling disproportionately one one group rather than another, or are leading to certain use-cases for data being left unrealised.
Re-framing the debate
I’m not calling for us to abandon a focus on standards. Indeed, much of the work I’m committed to in the coming year is very much involved in rolling out data standards. But I do want to invite us to think about framing our work on standards within a broader debate on interoperability and information quality (and ideally to embed this conversation within the even broader context of thinking on Information Justice, and an awareness of critical information infrastructure studies, and work on humanistic approaches to data).
Exactly what shape that debate takes: I don’t know yet… but I’m keen to see where it could take us…