Through a series of various types of meetings over the last couple of years I’ve been arguing the need to include notions of “inclusion” when discussing “open government data” and “openness” in general. My interventions along those lines are often greeted either with the dull stare of incomprehension; or with a quick nod of the head indicating agreement but with an equally quick averting of the eyes to indicate that the subject has no interest in this context and we should move on.
These results for my well-intentioned attempts to broaden and deepen the significance and audience for open data has generally left me feeling either frustrated or irritated or both.
And then I began to step back from the discussion and to examine it (and the overall ways in which open data is analysed and presented) in a broader and somewhat more philosophical light.
What is open data and is there more than one way to approach it?
Thus we have the definition of open data in “Open Definition”: “A piece of content or data is open if anyone is free to use, reuse, and redistribute it — subject only, at most, to the requirement to attribute and/or share-alike.”
Or that :
Open data is data that can be freely used, reused and redistributed by anyone – subject only, at most, to the requirement to attribute and sharealike.
The full Open Definition gives precise details as to what this means. To summarize the most important:
- Availability and Access: the data must be available as a whole and at no more than a reasonable reproduction cost, preferably by downloading over the internet. The data must also be available in a convenient and modifiable form.
- Reuse and Redistribution: the data must be provided under terms that permit reuse and redistribution including the intermixing with other datasets.
- Universal Participation: everyone must be able to use, reuse and redistribute – there should be no discrimination against fields of endeavour or against persons or groups. For example, ‘non-commercial’ restrictions that would prevent ‘commercial’ use, or restrictions of use for certain purposes (e.g. only in education), are not allowed.
Or we have the definition (taken at random) in this case from the City of Toronto: The City of Toronto makes data it collects available to the public via toronto.ca/open. By offering data sets for others to use, the City supports unfiltered access to its information.
If you go further down in the standard definition of “open data” this begins to become a bit clearer:
Interoperability is important because it allows for different components to work together. This ability to componentize and to ‘plug together’ components is essential to building large, complex systems. Without interoperability this becomes near impossible — as evidenced in the most famous myth of the Tower of Babel where the (in)ability to communicate (to interoperate) resulted in the complete breakdown of the tower-building effort.
We face a similar situation with regard to data. The core of a “commons” of data (or code) is that one piece of “open” material contained therein can be freely intermixed with other “open” material. This interoperability is absolutely key to realizing the main practical benefits of “openness”… (my emphasis).
That is, “open data” is a “piece of x (content, data, etc.)”, with the attributes and capabilities of rendering of a “thing” or “object” or “product” (a data set) that in turn can be “used”, “re-used”, “distributed” etc. Or, in other words it can be seen as a “component”, as a lego like building block which can be stacked one piece on another to create further and bigger objects. Thus it is to be seen as a “products” where “products” are “bought as raw materials and sold as finished goods” in this instance, where the raw data is the input and the “open data” is the output.
As an object or thing the attributes and characteristics of the open data are more or less fixed once made available to the end user/consumer. As well, the determination of the attributes or characteristics of the data (what the open data “is”) as seen/obtained by the end user is solely at the discretion of the producer and are uniform and stable as between end users.
But why shouldn’t we think of “open data” as a “service” where the open data rather than being characterized by its “thingness” or its unchangeable quality as a “product”, can be understood as an on-going interactive and iterative process of co-creation between the data supplier and the end-user; where the outcome is as much determined by the needs and interests of the user as by the resources and pre-existing expectations of the data provider.
We can define “service” as:
…a set of one time consumable and perishable benefits
- delivered from the accountable service provider, mostly in close coaction with his internal and external service suppliers,
- effectuated by distinct functions of technical systems and by distinct activities of individuals, respectively,
- commissioned according to the needs of his service consumers by the service customer from the accountable service provider,
- rendered individually to an authorized service consumer at his/her dedicated trigger
That is, redefining and re-conceptualizing open data as a “service” rather than as a “product” puts the emphasis on the “open” (and opening) as a transitive and interactive “process”, rather than as an “object”, and as an interaction and a relationship between the supplier and the end user; rather than the data (and its virtual “thingness”) as a once and for all discrete set of production and consumption activities.
Treating open data as a service rather than as a product implies a quite different approach to how open data is managed, in what form it is made available, how it is funded and what expectations are placed upon it by governments as suppliers and by end users.
Thus Open Government Data as a service:
- includes a concern for the end user and end uses in the overall planning and development
- includes those with an interest in end users and end uses in the project team
- recognizes the potential diversity and special needs of end users and their requirements for “effective use” including naive and inexperienced users–thus for example including the possibility of indigenous people, women, grassroots users, citizens and the public interest as possible end users and working interactively with these groups to make suitable provision
- applies a range of metrics to evaluation of the “success” of open government data including contributions to the public good
Why does this matter?
This matters because if one treats open data simply or exclusively as a thing or commodity then it is available solely as a product for purchase and use through the market place–where of course, market principles dominate and where for example, those with the most resources are able to command and control and thus precipitate the supply of the product i.e. the open data. This of course, fits quite neatly into the current neo-liberal agenda of certain governments of marketizing public services by first packaging them as discrete bundles of consumer oriented “products” and then opening up the processes of producing those bundles to competitive tender (as per the links that Jo Bates makes between Open Government Data and neo-liberal developments in the UK). However, whether such an approach is in the public interest is of course currently being severely criticized by those critical of what has been termed “market fundamentalism“.
Further, in this context the criteria of success or “value” of open data is exclusively based on its success in the marketplace as determined by market value, consumer demand, return on investment and so on. If however, one looks at open data as a service then the potential value of open data can be equally measured in terms of the benefits (including or particularly non-monetary) that the service is providing to the end user and to citizens as a whole.
As well, there is the possibility, even the requirement that open data as a service is directed towards the specific requirements of a diverse group of end users (and not simply anonymous interchangeable consumers) including for example, not-for-profits, community organizations, women’s groups, trade unions, and citizens working for the public interest amongst others and also would include the variety of adaptations, supports, training and so on which would maximize the opportunities for the various types of end users to benefit from the data service.
This of course, is particularly significant if one is concerned with ensuring that open government data is not simply “open” but also “inclusive”–that data that is provided by citizens is not simply privatized and sold off to the highest bidder but is made available in a form and a context where the broadest base of benefit may be derived from the data through its effective use by marginalized groups and citizens at large along with those who may be able to take a commercial advantage from making the data more generally available.