[April 2014] What Does the Post-2015 ‘Data Revolution' Mean for Human Rights Monitoring?

Publish Date: 
Wednesday, April 2, 2014

Last year, the UN High Level Panel on the Post-2015 Development Agenda called for a ‘data revolution’ to drive development. The term is both bold and imprecise. Perhaps because of this, it has generated great enthusiasm among a broad spectrum of actors expressing an even broader variety of interpretations of what this ‘revolution’ might mean.

At the end of January, I attended Data and Accountability for the Post-2015 Development Framework, a dialogue hosted by UNDP that brought together a diverse group of practitioners active in the field of data and accountability. Although human rights did not get much attention, a number of very relevant questions for rights monitoring were raised.


Data initiatives falling within the rubric of the data revolution include:

No doubt, there are varying degrees of familiarity with these types of initiatives. 


The prospect of better data has a lot to offer economic and social rights monitoring. Better demographic data, for example, makes it possible to uncover chronic and entrenched patterns of discrimination, while better financial data is crucial for assessing whether governments are using the maximum of available resources.

At the same time, there are ethical considerations involved in collecting, analyzing and disseminating data, and these risk being exacerbated by the data revolution. Big data can marginalize rights holders, for example, as researchers don’t even need to ‘parachute’ in; they can analyze a community in a hack-a-thon from half way around the world.


One major pitfall is that debate surrounding the data revolution has tended to follow a simplistic, linear theory of change, which fetishizes the power of data in and of itself. As Neva Frecheville from CAFOD has written, power has been largely omitted from the agenda.

There was a nod to this issue at the dialogue, with several participants raising the question: data + what = change?  I suggested that from the experience of rights monitoring, ‘data + in the hands of affected communities + translated into a rights claim + channeled through an accountability mechanism = change’. Another presenter, John Gaventa, identified the following conditions for data to be empowering:

  • Data: is accessible, understood, relevant, useable and  ‘owned’
  • People: are aware of rights and agency and have capacity and inspiration to act

Identifying best practices in how to create these conditions remains a pending task, however. How do we ensure that our use of data does indeed translate into meaningful change?


I see three crucial questions that determine whether data is empowering: What data is prioritized? How is data collected, analyzed and disseminated? And who is using data and for what purpose? Human rights can offer guidance on each of these questions. First, because they focus on conduct as well as result, human rights standards can help us demand “attributable” data. Several presenters commented that “attributable data”, which either shows responsibility of a particular decision-maker or that uncovers networks of power and privilege, is generally the hardest to attain. Second, with its focus on the principle of participation, a human rights approach helps to ensure that affected communities are driving the demand for data, as well as playing a role in framing data questions and validating findings, even if they are not collecting data themselves.


As Ben Taylor from Twaweza has written, “infomediaries” have a key role to play in making data meaningful for affected communities. These actors provide a ‘bridge between data and people’. They not only find stories ‘from screens full of numbers’, but also tell those stories in ways that engage and inspire citizens to act. 

In this way, those who monitor economic and social rights qualify as a type of infomediary. It remains unclear whether this is a role that activists and advocates will embrace, however. Do we consider ourselves to be infomediaries and, if so, is this a role we wish to strengthen? Sharing experiences of the issues involved in this endeavor may serve to identify challenges and opportunities for enhancing our data literacy.

Allison Corkery
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