At this week's ConDatos conference in Santiago, Chile, Network chief of research Stefaan Verhulst shared initial findings from the GovLab's collaboration with Omidyar Network around a selection of case studies on the impacts of open data. A companion blog post on the GovLab and Omidyar websites shares many of the insights from the presentation: 

Ways in which open data impacts lives

Broadly, we have identified four main ways in which open data is transforming economic, social, cultural and political life, and hence improving people’s lives.

  • First, open data is improving government, primarily by helping tackle corruption, improving transparency, and enhancing public services and resource allocation.
  • Open data is also empowering citizens to take control of their lives and demand change; this dimension of impact is mediated by more informed decision making and new forms of social mobilization, both facilitated by new ways of communicating and accessing information.
  • Open data is also creating new opportunities for citizens and groups, by stimulating innovation and promoting economic growth and development.
  • Finally, open data is playing an increasingly important role in solving big public problems, primarily by allowing citizens and policymakers to engage in new forms of data-driven assessment and data-driven engagement.

Enabling Conditions

While these are the four main ways in which open data is driving change, we have seen wide variability in the amount and nature of impact across our case studies. Put simply, some projects are more successful than others; or some projects might be more successful in a particular dimension of impact, and less successful in others.

As part of our research, we have therefore tried to identify some enabling conditions that maximize the positive impact of open data projects. These four stand out:

  • Open data projects are most successful when they are built not from the efforts of single organizations or government agencies, but when they emerge from partnerships across sectors (and even borders). The role of intermediaries (e.g., the media and civil society groups) and “data collaboratives” are particularly important.
  • Several of the projects we have seen have emerged on the back of what we might think of as an open data public infrastructure – i.e., the technical backend and organizational processes necessary to enable the regular release of potentially impactful data to the public.
  • Clear open data policies, including well-defined performance metrics, are also essential; policymakers and political leaders have an important role in creating an enabling (yet flexible) legal environment that includes mechanisms for project assessments and accountability, as well as providing the type of high-level political buy-in that can empower practitioners to work with open data.
  • We have also seen that the most successful open data projects tend to be those that target a well-defined problem or issue. In other words, projects with maximum impact often meet a genuine citizen need.

Challenges

Impact is also determined by the obstacles and challenges that a project confronts. Some regions and some projects face a greater number of hurdles. These also vary, but we have found four challenges that appear most often in our case studies:

  • Projects in countries or regions with low capacity or “readiness” (indicated, for instance by low Internet penetration rates or hostile political environments) typically fare less well.
  • Projects that are unresponsive to feedback and user needs are less likely to succeed than those that are flexible and able to adapt to what their users want.
  • Open data often exists in tension with risks such as privacy and security; often, the impact of a project is limited or harmed when it fails to take into account and mitigate these risks.
  • Although open data projects are often “hackable” and cheap to get off the ground, the most successful do require investments – of time and money – after their launch; inadequate resource allocation is one of the most common reasons for a project to fail.

Read more here

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