Table 1.

Effect on analytical policy capacity of non-traditional data use across case studies

Case nameCountryPolicy cycle stageEffect on analytical policy capacityMain reference
decidim.barcelonaSpainAgenda-settingSystemic: public opinion influences agendaPeña-López (2017) 
Organisational: meta.decidim, a community with representatives of citizens and civil actors, is responsible for designing and updating decidim.barcelona
Individual: training sessions by public officers to enable citizens’ e-participation; data analysis and aggregation for the prioritisation of policy agenda by part of the Municipality
Call detail records data for COVID-19 responseGambiaPolicy formulation/decision-makingSystemic: not clear/accessibleArai et al. (2021) 
Organisational: collaboration between Public Utilities Regulatory Authority (PURA), The Gambia Bureau of Statistics (GBoS), Ministry of Health, mobile network operators; a secure file transfer protocol (FTP) enables transfer of data from third parties 
Individual: use of the Hadoop platform for distributed processing of large data sets; strengthening of data collection protocols 
Automated verification of medical prescriptionsPortugalPolicy implementationSystemic: not clear/accessibleAlgorithmWatch (2020) 
Organisational: improved data collection through the electronic medical prescription system; access to an integrated data system of the Public National Health Service (NSN)
Individual: data processing by part of Control and Monitoring Centre
Santa Monica Well-being ProjectUSAPolicy evaluationSystemic: direct access to publicly available data through social media platformOECD (2017) 
Organisational: enhanced connection with non-governmental institutes (i.e., research units) responsible for developing measurement
Individual: use of the Wellbeing Index as a framework for planning the budgets and programmatic priorities; commissioned/outsourced data collection and aggregation activities

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