This hands-on workshop was the first of two consecutive workshops that used civil society corruption datasets to explore and analyse the Comparability element of the DataShift. Following the data expedition model established by the Open Knowledge Foundation’s School of Data, anti-corruption campaigners were asked to explore working with civil society corruption data, with the objective of testing the limits of comparability and analysis within existing datasets. While the corruption theme was chosen due to extensive existing data in the area (such as Transparency International’s Corruption Perceptions Index, I Paid a Bribe Kenya, Morocco – Mamdawrinch Reports), the workshop’s key outcomes are applicable while exploring post-2015 people-powered monitoring for all of the Sustainable Development Goals:
- Data harmonization needs to be a rigorous process that considers differences in scope, geographic relevance and comparability, temporal coverage, and linguistic differences.
- While creating data standards makes Comparability possible, collection may still be difficult; capacity building in data collection is crucial.
- Data comparison can be an effective Campaigning tool to show a measured factor’s change over time, its correlation with other variables, and creating a vertical connection between local, national, regional, and global actors.