The goal of the Web Foundation’s open data research programme is clear. We want to equip policymakers and shapers with actionable insights to ensure that open data becomes a powerful tool for development, particularly in the Global South. In line with this mission, in 2014 we completed the first phase of our Exploring the Emerging Impacts of Open Data in Developing Countries (ODDC). This phase – ODDC1 – was an important first step, but we knew we had to go further. So, we embarked on ODDC2 – further synthesis research around common themes which arose across many of the projects. We deliberately chose not to focus on the technical aspects of open data, but rather on the social, political and legal aspects required to build a thriving open data community – one which is capable of using open data as a tool to improve the day to day lives of citizens. The results of these projects are available here.
How can developing countries secure the full benefits of open data? What barriers are blocking greater impacts? And how can open data be implemented in ways that respond to local context, and that build on existing policy and practice of foundations?
To address questions like these, the Exploring the Emerging Impacts of Open Data in Developing Countries (ODDC) research network has been gathering information on open data activities across 13 different countries on three continents. Using a mixed-methods case study research, 17 local research partners have developed in-depth accounts on the supply, mediation and use of open data in diverse settings: from budget scrutiny to oversight of judicial systems.
This briefing offers 15 initial insights generated from a preliminary synthesis of this research, offered as a basis for further conversations.
Every day, national, regional, and local governments spend vast sums of citizens’ tax money. However, all too often, there is a lack of transparency around how these public funds are spent. In Indonesia and the Philippines, civil society groups have consistently clamoured for more accountability in public finances in areas such as procurement, education, and infrastructure. This paper summarises the approach we used and the lessons we learned as we explored how open data might best be harnessed for fiscal transparency in the region.
The Web Foundation’s Open Data Lab produces how-to guides that outline step-by-step the different approaches used in their projects. Some of the Guides are:
1. Opening Data from the Ground Up: This is our step-by-step guide on how we worked with the education agency in Banda Aceh to open up data that was in demand by civil society, as well as how we supported civil society organisations to make use of the data to improve the quality of education in their city.
2. Leveraging Open Data for Greater Fiscal Transparency: This How-to Guide is intended for organisations with expertise in open data, who would like to help civil society groups strengthen their fiscal transparency work through open data. It is also intended for government agencies with established open data initiatives who want to strengthen user engagement and increase citizen participation.
3. Fostering Government and Civil Society Collaboration through Open Data: This guide suggests specific steps that can be taken by funding agencies, project implementers, and other stakeholders who want to promote collaboration between government and CSOs through the use of open data. This approach is particularly helpful in a context where there is prevailing distrust and animosity between the two groups, as it can ensure collaborations are based on facts, not opinions.
4. Accessing and Making Use of Open Health Data: This guide is written for donors, civil society organisations, governments, and other stakeholders who would like to build capacity of user groups in accessing and using open health data to improve their advocacy or development work. In some cases, user groups will be entirely new to open data. Others might have experience using health data, but are unaware of better ways to find datasets efficiently and/or struggle to make effective use of them.
In 2015 the Open Data Inventory (ODIN) assessed the coverage and openness of official statistics in 125 mostly low- and middle-income countries. Data in 20 statistical categories were assessed on 10 elements of coverage and openness. The assessments are objective: they record whether data are available and whether the data conform to standards for open data, but they do not attempt to assess the quality of the data. They also record the online location of the data, allowing others to verify the results.
ODIN scores are summarized by data categories and by the elements of data coverage and openness, creating a profile of each country’s statistical system and its ability to deliver the information needed by governments, citizens, and the private sector to guide their decisions. In 2015 no country’s ODIN score reached 70 percent of the total possible points. The highest scoring country was Mexico, with a score of 68 percent, followed closely by Moldova and Mongolia. Rwanda, with a score of 59 percent, was 4th overall and the highest scoring country in Africa. The lowest scoring countries were found in parts of Africa, Asia, and Europe. Measured just on the elements of openness, Mexico was the clear leader with a score of 74 percent, followed by Rwanda and Moldova. Measured by data coverage, which considers the availability of key indicators over the last 10 years and for sub-national units, Cuba had the highest score, followed by China and Moldova.
There is more to be learned from the ODIN assessments. This first annual report on the Open Data Inventory describes the assessment process and highlights significant patterns in the results. The appendixes list results for 125 countries and provide greater details on the assessment methodology as well as orientation for obtaining ODIN results online.