The University of Warwick, in collaboration with the Alan Turing Institute, ran DSSGx UK 2020 online, due to the global pandemic. Four teams worked on a range of diverse projects, delivering a success solution to the project partners.
The DSSGx 2020 projects:
World Bank – Identifying and analysing corruption risks in public administration
A collaboration with the World Bank investigated how cutting-edge data science methodologies can link public procurement data and the asset declarations of public officials to support the identification and analysis of corruption risks in public administration. This will allow practitioners, policy makers and civil society to inform policy responses and address corruption risks in the public sector.
The increasing availability of machine-readable open data generated by governments is improving the ability to analyse and understand corruption risks. The initiative will help address the gap of analytical frameworks and data driven methods that are needed. It will explore how big data and machine learning methodologies can support the analysis of the scale, mechanics and impact of corrupt practices within public administration to help increase accountability and integrity in the public sector. The DSSG project will contribute to the World Bank’s broader anticorruption research programme and the technical advice it provides to governments.
Ofsted - Risk Assessing Early Years Providers
The goal of the project was to use a range of data both held by Ofsted and publicly available to build a risk model that identifies early years providers (child minders and nurseries) that are at risk of providing sub-standard care.
DSSGx 2020 - Ofsted - Risk assessing early years providers