iHub Research Data and Visualisation Lab

Cite as:

Okune, Angela, Philip Ochola Mak'Anyengo, Sylvester Wachira Ndaiga, Sidney Ochieng, Rhoda Omenya, Chris Orwa, Nanjira Sambuli, and Varyanne Sika. 2018. "iHub Research Data and Visualisation Lab." In "iHub Research (2011 - 2017): A Critical Technology Action Research Group Within Nairobi's Flagship Tech Innovation Hub," created by Okune et al. In STS Across Borders Digital Exhibit, curated by Aalok Khandekar and Kim Fortun. Society for Social Studies of Science. August.

Meta-Narrative

The iHub Research Data Science & Visualisation Lab was designed to provide data support and resources to iHub Research projects while at the same time providing an avenue for consultancy services on the innovative use of data and technology. The Data Lab was especially focused on working on the data life cycle from data collection, data storage, and analysis, data visualization. The Data Lab, like the iHub Research Build Lab, was unique in its approach to both develop as well as study the process of developing machine learning technologies. This approach emerged from lessons learned over time at iHub Research and required a diverse team that included computer engineers, experts in servers and data storage, graphic designers, and social scientists.

This PECE essay helps to answer the STS Across Borders analytic question: “What people, projects, and products exemplify how this STS formation has developed over time?

This essay is part of a broader exhibit on iHub Research.

STS Across Borders In Brief

STS Across Borders is a special exhibit organized by the Society for Social Studies of Science (4S) to showcase how the field of Science and Technology Studies (STS) has developed in different times, places...Read more

Mutuku, Leonida and Mahihu, Christine. 2014. "Open Data in Developing Countries." Final Report. iHub Research.

AO: The Open Data in Developing Countries Project run by iHub Research set out to understand initial impacts of the Kenya Open Data Initiative (which was launched in 2011). The study found that three years after the launch of the data initiative, there has not been substantial documentation of...Read more

Blog post: "Kenya's Low Consumption of Open Data"

AO: This 2013 blog post by Christine Mahihu highlights the low use of Open Data in Kenya since the launch of the Open Data Initiative in 2011 and highlights some of the challenges and opportunities.Read more

Example Projects that both developed and studied the implementation of Machine Learning:

AO: The Umati project and 3Vs projects are two examples where data scientists worked together with social scientists to both develop and study the process of developing tools based on machine learning technologies.

Building an Intelligent Umati Monitor (2015)

AO: This artifact is one of the reports from the second phase of Umati.Read more

Data Science & Viz Lab Slide Deck (2013)

AO: This slide deck introduced the iHub Research data lab to the community and was used during a public event in 2013.Read more

"Can you explain a bit more about what iHubR data science was?"

Sidney Ochieng (July 2018): "The Data lab was the data processing arm of iHubR. It was started to begin take advantage of big data technology to do research and provide solutions in that vein. It was also helped build data science skills and promote the use of the tech in Kenya. It also highlighted pioneers of data science locally."

Chris Orwa (July 2018): "The iHub Research data science initiative was initially a unit within the research team that provided in-depth analysis to researchers. Later it spun out to be one of the departments within iHub. While being housed at iHub Research, my role was of a data scientist in which I performed machine learning on large sets of data, developed tools for scraping data and coordinated work for build automation tools for the research team. Later I was the lead for the data science unit at iHub and my responsibilities were to develop analysis methodologies, manage people and look for business opportunities where data science can be used to solve problems. In addition to crafting research projects around data, and building Data Science capacity within the institution and the larger iHub community."

"What kinds of groups did the data lab engage with? Who was/is interested in data science in Africa?"

Sidney Ochieng (July 2018): "The data lab worked with researchers, NGO and for profits. These days everyone is interested in DS in Africa."

Chris Orwa (July 2018): "The Data Science Lab team engaged two types of groups; upcoming data scientists and industry practitioners. In Africa, technology starts up formed the bulk of people interested in data science – it was  a focus on how they could use data science to make their products better. Projects under the mandate of the data lab ranged from predicting rainfall using satellite images in Tanzania to developing data sharing protocols for 8 Eastern African states. These incorporated machine learning work and data policies and laws."

July 2018

Examples of Data Lab alumni and what they are up to

Chris Orwa (July 2018): "Currently I work at Safaricom PLC as Data Scientist. Our department is tasked with innovating products for the main business from a data perspective. We therefore work on issues that affecting customers by understanding their behaviors through the data collected."

Sidney Ochieng (July 2018): "Currently I’m the Chief Data Scientist at Intelipro and a consulting data scientist. At Intelipro I build credit scoring and do consumer analytics. As a consultant I currently work with an NGO as the technical data lead on a project helping them build their data pipelines and analytics."