Methodology
‘Spotlights’ is a comprehensive online resource that brings together a range of official publicly available data on Kenya and Uganda under one roof. It provides data and visualisations on key socio-economic indicators and financial flows at the subnational level, highlights key data gaps and supports the increased use of data and information to reduce poverty and promote sustainable development.
Geospatial framework
The data is stored and presented within a geospatial framework that is based on each country’s administrative subdivisions. Data is presented with the same level of geographic disaggregation as when it was originally published. The data for Kenya focuses on counties and sub-counties while the data for Uganda focuses on districts.
Topic areas
The data is organised into six areas: poverty and vulnerability, population, education, health, water and sanitation and district public resources. Each topic is split into various key indicators providing detailed information ranging from proportions of those with a disability to student-teacher ratios and the proportion of births attended by skilled personnel. In our 2020 update we will include additional data from infrastructure, disaster risk reduction, labour force and housing.
Data sources
The data for Kenya is sourced from the Kenya National Bureau of Statistics, government ministries, county budgets, the DesInventar database and the Office of the Controller of Budget.
Most of the data for Uganda is sourced from the Uganda National Bureau of Statistics. Additional data for Uganda is sourced from publications and datasets from various sectors and line ministries. National examination performance data is not always made public; it is sourced from Uganda open data portal.
Data collection and quality control
Data collection starts with identification of an official source, followed by making a request for the data from the source if it is not publicly available and accessible. Data comes in various forms – some come in machine-readable formats search excel, CSV or other formats that are readable with statistical software like SPSS, SAS or STATA, while some come in PDFs and text formats. All data that comes in non-machine-readable formats such as PDFs are scraped and converted back to machine-readable formats. This data then goes through validation to see whether the data contained in the CSV files is a true reflection of what is in the PDFs. The data is then sent to the developers who update the website.
Timeliness
The spotlights include data from a variety of sources, each with their own production and publishing cycles. Every attempt is made to refresh the spotlights in a timely manner when the updated source data becomes available.