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Drt findings presentation


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Presentation on 'How Open data could contribute to poverty eradication in Kenya and Uganda through its impact on resource allocation'

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Drt findings presentation

  1. 1. How open data could contribute to poverty eradication in Kenya and Uganda through its impacts on resource allocation: Research Findings BERNARD SABITI – Presentation to the Dissemination workshop, Hotel Africana, Kampala, Uganda June 5, 2014
  2. 2. Objectives Overall objective: Use case studies from Uganda and Kenya to trace the evolution of the open data movement in the two countries and to assess the role that this movement plays in accountability and the equitable allocation of financial resources for the eradication poverty
  3. 3. Research questions: 1. How are open data initiatives in Uganda and Kenya contributing to poverty reduction through impacts on resource allocation? 2. How could the contribution of open data initiatives to poverty reduction resources allocations be strengthened in the future?
  4. 4. Definition of terms 1. “Open Data”: Data which is made accessible (usually online), in a standardized machine-readable format, and under a license that allows it to be re- used 2. Open Data Initiative: any organized activity focused on providing open data (Supply side), or on securing access to open data (demand side) source:
  5. 5. Definition of terms 3. Open Government: A campaign that started in 2009 with the presidency of Barack Obama. Advocated for ‘putting government online’. Open Government Partnership founded in 2009 and launched in 2011, initially with a membership of eight countries but which has since grown to 63 (In East Africa, Kenya and Tanzania are members but Uganda has not yet signed up)
  6. 6. Definition of terms Resource Allocation: The decisions of policy makers and duty bearers to distribute money, manpower, public goods and other efforts to sectors, regions, or otherwise, for development purposes Poverty Eradication: The desire and efforts of most national and international development actors to end poverty (by 2035)
  7. 7. Our Key Assumptions Data • Data on:Social ecc indicators, resource flows, use and misuse • available • accessible • useable to • CSOs, media, MDAs, Decision makers • MDAs • Politicians • Donors make more informed decisions on resource allocation and use Resource Allocation • more resources allocated to education, health, Agriculture, and other poverty reducing sectors Poverty Eradication • Better Development outcomes • Better use of resources • more accountability • more transparency
  8. 8. Methodology 5 stage process (March 2013 –April 2014) Inception phase Literature review Consultation Analysis phase reporting and feedback phase.
  9. 9. Methodology Data collection Semi-structured Interviews with KIIs from CSOs, MDAs, Donors, academia and private sector. MDAs 35% Academia 15% CSOs 31% Private sector 8% Donors 11%
  10. 10. Methodology cont’d: some respondents Kenya Uganda Ministry of Information and Communication ICT Board Uganda Bureau of Statistics iHub Research Ministry of Finance Budget Monitoring and Accountability Unit (BMAU) University of Nairobi Ministry of Education (Directorate of information) The National Treasury (E-ProMIS National Information Technology Authority (NITA) Strathmore University, iLab Africa Collaboration on International ICT Policy in Eastern and Southern Africa (CIPESA) TradeMark East Africa Anti Corruption Coalition of Uganda (ACCU) African Media Initiative (AMI) Knowledge Management and Communication Capacity Initiative (KMCC) Ministry of Devolution & Planning Northern Uganda Media Club (NUMEC) Kenya National Bureau of Statistics Rwenzori Information Centres Network (RIC-NET) World Bank Country Office UNICEF (Devtrac) Kenya ICT Authority GIZ (Ministry of energy data project) Economic Policy and Research Centre (EPRC)
  11. 11. Methodology cont’d Case studies •Kenya Open Data initiative •E-promis (electronic Project Monitoring Information System in Kenya’s MoF) •Uganda’s •BOOST •Kasese E-society resource centre (RIC-NET) •Devtrac
  12. 12. Analytical and conceptual framework In order to assess the role of open data in resource allocation for poverty eradication in Kenya and Uganda, we adopted a holistic “ecosystem” analytical framework
  13. 13. Findings What is the current status of Open Data in the two countries?
  14. 14. What is Open Data in the two countries? Different from the Open Definition. Data dissemination still very traditional (more so for Uganda than Kenya)
  15. 15. KODI:
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  17. 17.
  18. 18. Ureport
  19. 19. Uganda Open Development Platform –
  20. 20. Dimension Drivers Legislative/statutory environment The ICT policies (in both countries) Institutions like Kenya ICT board, Uganda National IT Authority, ministries of ICT provide conducive policy environments. Freedom of information act (bill for Kenya’s case) Economic The availability of funds through a development partner (WB) played a role in the early success of KODI. Donors demand data for their planning activities, and are increasingly pushing for general open data policies. technological Increasing internet penetration and other ICT modern infrastructures like smart phones, and general access to these technologies SocioPolitical Political will exists in some quarters of the governments A government champion in Kenya’s Communications ministry was key to KODI Drivers and Barriers of Open Data Processes in Uganda and Kenya
  21. 21. Barriers Dimension Barriers Policy/Legislative •Antiterrorism laws e.g Kenya media bill (2013) – vetoed by president •Communications Regulatory Authority Bill, 2012 •The Regulation of Interception of Communications (RIC), 2010 •The Anti-Terrorism Act No.14 of 2002 •Press and Journalist Act •Public Order Management Act (2013 •The computer misuse act of 2010 Economic The absence of funding has played a role in Uganda’s initiative by making it difficult to launch. So whereas there is some political will in both countries, funding was the main difference in the existence of the initiatives. Donor demand focuses on their core interests like aid and statistical information; yet open data should cover broader scope ICT Digital divide: Internet coverage is poor in rural areas where majority of the people live. SocioPolitical Some politicians are suspicious if skeptical of open data movements and offer only tepid support. The most enthusiastic about it are not very powerful and influential in decision making. Custodians of data consider it to be their power tool and so hold onto it. (Data hugging,) Apathy from the public and officials
  22. 22. F g Findings II Key messages
  23. 23. g Findings cont’d •Although there was no clear link between open data and resource allocation, largely because of political economy factors, the potential for this link is apparent because of strong drivers of open data processes in both countries. •While the progress so far realised on openness in Kenya is driven by ICT growth, in Uganda it is driven more by low-tech, traditional transparency initiatives. •A digital divide between rural and urban; male and female regarding access to open data drivers is evident in both countries. •In both countries, the legal and policy frameworks are robust. However, the very governments that have created these robust frameworks have also found ways around the legislative framework to ‘undermine’ openness and transparency.
  24. 24. g Findings •In Kenya greater focus needs to be on strengthening the political and legal aspects of open data while facilitating multi- stakeholder engagement In Uganda on the other hand, financial investment in the open data process, building multi-stakeholder engagement, strengthening the legal and political environment and capacity building emerged as some of the key areas of focus. • There is still a preference within governments for the traditional way of data collection, management and dissemination in form of voluminous books and highly technical terminology. •There is need for open development championing institutions (individuals, civil society, private sector, media, academia) •There are multiple actors within the data ecosystem, who however, work in silos not complementing each other’s efforts. Linkages must be therefore created to ensure efficacy.
  25. 25. g Recommendations For Governments •Promote sector and cross sector specific initiatives that enable collaboration and transparency through different e- transformation strategies across government sectors and agencies • Formulate and IMPLEMENT policies, regulations and laws to support the use of ICT to transform service delivery •Provide an environment that allows an open government and civil society to participate in content and service creation in both countries.
  26. 26. g Recommendations For CSOs •Create awareness and a culture of open data in Kenya and Uganda by explaining what it is, who it serves and why the country needs an open development approach in national development •work in partnership to strengthen their voice in advocacy for transparency and accountability through availability and access to public data
  27. 27. g Recommendations cont’d For Private sector and the ‘techies’ •To work with government, CSOs and other actors to increase investments in technologies and services that promotes access to data and information. •Contribute to the bridging of the rural-urban digital divide that exists by ensuring penetration into rural areas, cost effectiveness and affordability of information technologies
  28. 28. g Recommendations cont’d For Media •Adopt and embrace the growing culture of data journalism •Provide free or affordable space for dissemination of critical data aimed for the public good. E.g Data on the state or investments in water, education, agriculture and other poverty related sectors
  29. 29. g Recommendations cont’d For Data Producers Always endeavour to avail data in easy to use, machine readable formats, in addition to the existing traditional formats (such as big books, newspaper pullouts, notice boards and PDFs)
  30. 30. g Recommendations cont’d For Citizens: Demand for update, regular, simplified and digestible data from government on resource allocation and other development matters.