Accessing and using data

In most cases, data needs to be processed for it to be useful. It must be processed and used – displayed visually, built into a service or decision-making tool, or used as part of a campaign, for example.

An early article on open data described the assumption that “by making data publicly available in re-usable formats, society would take care of building applications and services” (Huijboom & van den Broek, 2011).  This is done by intermediaries (or ‘infomediaries’): people and organisations positioned at some point in a data supply chain who facilitate the use of released information (van Schalkwyk et al., 2015). They can include app developers, journalists, researchers, civic technology activists, and others who can either react to insights or disseminate them so others can do so. (See Carter (2016) for more on infomediaries and accountability.)

However, the assumption that data made available will naturally be put to use may not be correct in the context of international development. Individuals and organisations may not have the necessary skills, motivation, capacity, tools and space to find, process, use and share data and anything that is built from it. One paper calls public interest in the reuse of open public data a “myth” (Hellberg & Hedström, 2015).

Capacity can be limited, to the exclusion of certain groups including women and rural populations. A study of the impact of open data and transparency on poverty eradication in East Africa found that limited technical capacity in data production, analysis and usage, compounded the disparity between literacy levels among men and women (see Lwanga-Ntale et al., 2014 and Neuman, 2016).  This is problematic for two reasons. First, it can lead to unequal access and therefore unequal benefit from using the data. Second, there are questions as to whether insights or services created will therefore disproportionately benefit that group or those of a similar demographic.

Elections in Indonesia

Kawal Pemilu (“Guard the Election”) was launched after the 2014 presidential elections in Indonesia as the two contenders traded allegations of vote rigging. A group of technologists and volunteers created a website allowing citizens to compare official vote tallies with the original tabulations from polling stations. The tabulations were made public as part of the Elections General Commission’s commitment to openness, but 700 volunteers had to digitise the forms and make the data more accessible. GovLab’s case study found impact in enabling citizen participation, increasing trust in official tallies and easing the democratic transition.

Source: Graft et al. (2016a).

Some examples, however, show the potential for intermediaries to drive accountability through analysis of data in developing countries, including the example of the 2014 presidential elections in Indonesia.

Intermediaries can also play other important roles beyond data processing. The IBP reviewed 21 case studies and found that civil society played a bigger role in bridging the gap between transparency and accountability than is often recognised. As intermediaries, civil society can make up for the deficiencies of formal oversight actors and improve the accountability system in four main ways (van Zyl, 2013):

  • accessing, interpreting and distributing information to multiple stakeholders in useable and accessible formats
  • demanding accountability of government directly
  • supporting and encouraging formal oversight actors to demand accountability (such as legislatures, auditors, judiciaries)
  • supporting and encouraging other actors to demand accountability (such as executive insiders, political parties, donors)

In India, for example, demands by women for accountability in wage payments led to a digital wage payment and tracking system, whereby individual rural women and local organisations could compare biometric-based attendance systems at worksites and online publication of muster rolls and wage records (Rajput & Nair, 2011). A further example of civil society using open data to prompt oversight was the 2009 Afghan elections.

Mapping elections data in Afghanistan

Following the 2009 election in Afghanistan, a map built using released open election data quantified the extent of fraud. It showed that in many polling stations returning a high ballot count a single candidate had received over 90% of the votes. This map informed the decision to force a runoff. The project was repeated in 2014, and included a data exploration tool allowing the identification of anomalies. In one region, results showed Ashraf Ghani winning 100% of 600 ballots in well over 100 stations.


Engagement with intermediaries and other potential or actual users of information has been highlighted in both the transparency and open data literature as important to the success of initiatives (Davies & Bawa, 2012; Zuiderwijk et al., 2012; Peixoto, 2013; Lindstedt & Naurin, 2010).

In a review of evidence from social accountability initiatives, Fox (2014) found that the most effective projects open up citizen engagement beyond the local arena and increase government’s capacity to respond. A study of Spanish and German initiatives found that failing to integrate external data users led to a proliferation of low-value datasets being published (Hunnius et al., 2014). Another found that, even where power relationships between aid accountability seekers and agents are unequal, the fact that a relationship is constructed and maintained at all was key to effectiveness and impact (McGee, 2013).