Monthly Archives: January 2015

About Joined Up Data Uganda (JUDU)

By Bernard Sabiti

Primary school grades data displayed at a noticeboard in Katakwi District

Primary school grades data displayed at a noticeboard in Katakwi District

Despite the abundance of open data available from various sources, the right data is still not there in many developing countries which will allow policymakers and citizens to understand how resources spent in their localities (by the multiple funders at work) will affect their community, their school, or their health centre. More importantly for local stakeholders, social data- which could help decision-makers understand the wider impact of social projects at district level – may be available, but is not currently interoperable with expenditure information.

Since February 2014, Development Initiatives with her local partner Development Research and Training have been implementing a Gates Challenge grant to create a pilot model of an ‘open resource toolkit’ by collating all available data on social spending in two specific sectors, within specific trial localities, to maximum granularity –while building interoperability with social impact data.  This innovative ‘data partnership’ project will provide evidence-based recommendations government stakeholders who see interoperable data for poverty eradication as a necessary public good. We called this undertaking, Joined Up Data Uganda (JUDU).

For the Start, we began with two districts, seeking to understand the data situation around the two sectors of Health and Education, and with a baseline study sought to understand the situation in Kitgum and Katakwi. The needs assessment was intended to establish the districts’ capabilities of proper data management. We set out to identify the data collection and storage infrastructure by creating an inventory of different equipment and capacities, from hard and software to interpretation, dissemination and messaging capacities. Specifically, we wanted to:

  • Understand what data is available and in what format, how they are collected, by who, accessibility, demand, etc. i.e. management
  • Assess what data exists on sectoral outcomes in these sectors( ‘Results datasets’) and,
  • Understand who the users are and what their experiences are

We found that districts face a myriad of challenges which include;

  • Unreliability of data: the methodologies employed (by both government and non-state actors) in data collection and tools used in analysis and execution needs to be validated for reliability and comparability.
  • Human Resources- Staffing gaps, lack of sufficient expertise at different levels to generate, analyze, and synthesize data
  • Limited financial resources to collect, update, process, store and share data
  • Technological challenges – Unstable electric power, computers crushing where available, etc
  • Non- machine readable data (most keep it in hardcopies)
  • Bureaucracy and long, comprehensive procedures to access data
  • Missing data due to changing staffs in departments and poor handover processes
  • Lack of functioning website due to lack of IT specialist and funds for hosting and regularly update it

With this experience in mind, our project seeks to localize the global data revolution debate by going with the basics first. We believe that the local contexts and realities are not amply acknowledged at the international level and part of the reason is that there isn’t enough knowledge out there about these realities.

  • The standard open data portals operate in silos and in most cases do not advance the objectives of open data, the most important of which is easy universal access
  • Many players are producing data which is fragmented and disjointed that it doesn’t tell any stories
  • Procedures to access data as well as secrecy laws that remain on the books all discourage data access.

The joined up data project’s ultimate aim is that expenditure data is interoperable with results data, and that data is turned into information. Our theory of change is routed in the core problem of emphasizing just data:

“Data is good but it becomes better when it is analyzed; Analysis is good but it becomes better when it makes good messages; Messages are good but they become better when they can be translated into good policy and practice; Policy and practice is good but only useful when it provides a platform for interlocking, interacting and networking of stakeholders.” – One of our Directors.

For more information, download the progress report, or see the  project inaugural blog