Open Data and Civil Society Networks in Kenya

Alex Kostura
(I am not taking the second module)

RESEARCH QUESTION:

What is the effect of the Kenya Open Data Initiative on networks of anti-corruption civil society organizations in Kenya? Can social network analysis help explain why the Open Data portal is under-utilized?

CONTEXT:

Open data is data that is made available by organizations, businesses and individuals for anyone to access, use, and share – The Open Data Institute [i]

Open data as an idea represents both a new trend in international governance and an emerging field of study across disciplines as diverse as democracy, economic development, and urban planning. For my capstone project, I am specifically looking at the idea of open government data and the growth in “open data initiatives” where local, regional, and national governments create a web portal to publish data for public consumption. Two distinct civil society movements have evolved around open data: one that focuses on human rights and the other on accountability and government transparency. I am looking at the latter through a case study into Kenya’s Open Data Initiative.

In 2011, the national government of Kenya launched the Kenya Open Data Initiative (KODI) with praise from the international community and broad government support. This web portal promised its data to be the “key to improving transparency; unlocking social and economic value; and building Government 2.0.” [ii] Three years later, a 2014 study titled “Open Data in Developing Countries” found that Kenyans have little knowledge of the open data portal and it is underutilized as a result.

MOTIVATION and HYPOTHESIS:

This analysis will be part of a larger case study looking at the effect of open data initiatives on transparency/accountability in countries where corruption has historically been an issue. My hypothesis is that a network of non-governmental and civil society organizations (CSOs) builds up around the implementation of the open data initiative. And the Open Data Initiative itself is only as effective as this network’s ability to analyze and distribute data, garner public support, and advocate to the government. Thus, I am hoping a social network analysis will reveal the strength and connectedness of this CSO network.

DATA:

Based on open sources, I will construct the network of CSOs working nationally on transparency and accountability issues. The nodes for this network will be organizations. I will potentially create three networks:

1)   Ties determined by whether or not they participated in the coalition advocating for the creation of the KODI. 0 =  Did not participate; 1 = Did Participate

2)   Ties determined by partnerships or working relationships. Organizations would respond to the question “How often have you collaborated or shared information with another organization in the past year?”   Answers would be valued 0-Never, 1-Not very often, 2-Frequently

3)   Ties determined by sources of information. Organizations would respond to the question, “Which organizations do you go to as sources of information?” Answers would binary with 1 indicating a source of information.

I would seek the following attribute data:

·      International or National Organization

·      Parent/Affiliate Organization

·      Membership size

·      Staff size

·      How often does organization access the KODI data portal?

·      Number of reports produced

·      Website?

·      Social media presence?

·      Location of office

·      Working languages

Data would be collected via open sources and a survey of target organizations. Depending on the number of organizations identified with transparency and accountability missions, data collection could be unwieldy. Data collection would likely be incremental, and the list of organizations included in the network will likely grow with each group surveyed.

ANALYSIS:

Because I am analyzing a newly constructed network, I would run multiple cohesion measures and look at density, connectedness, average degree, components, diameter and average distance. These initial whole-network measures would inform next steps for analysis. For example, I might conclude that the network is fragmented by cliques or subgroups. It would also be interesting to look for structural holes where organizations with very similar missions are not connected. I would likely run this analysis on a network that only includes the coalition of those who advocated for the KODI’s creation initially.

Node centrality measures would also be useful in identifying organizations who may serve critical roles in ensuring the open data ultimately strengthens civil society networks. These include:

·      Nodes with high in-degree centrality in the “information network” may be identified as sources of information. These organizations are likely ones that have the technical capacity to download, analyze, and interpret government data. They might be targeted to lead data training.

·      Nodes with high betweenness in this network may be identified as brokers who connect nodes with organization with different expertise.

·      In the collaboration network, nodes with high in-degree and out-degree eigenvector centrality may be identified as potential leaders who will be key to strengthening the network.

 Additionally, it would be useful to analyze the network based on who currently accesses the KODI and who does not. Looking at this network would ideally reveal how open data is making its way through the network; and if it is not, how could Kenya's civil society improve that?

PREVIOUS RESEARCH:

David J. Marshall and Lynn Staeheli, “Mapping Civil Society with Social Network Analysis: Methodological Possibilities and Limitations.” Geoforum. Volume 61, May 2015, pp.56-66

Social Network Map of Civil Society Organizations with Partnership Ties and Donor Ties:

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[i] http://theodi.org/guides/what-open-data (accessed October 22, 2015)

[ii] https://www.opendata.go.ke/ (accessed October 22, 2015)