STRATI Journal of Data Science for Public Policy

The Journal aims to:

• Advance the integration of data science methodologies into public policy analysis and evaluation.
• Promote rigorous empirical studies that use novel datasets and analytical tools to inform policy debates.
• Provide insights into how data-driven approaches can enhance transparency, accountability, and citizen engagement.
• Explore ethical, privacy, and governance issues surrounding data in public decision-making.
• Foster collaboration between data scientists, policymakers, academics, and civil society.

Scope includes (but is not limited to):

• AI and ML applications in governance and policy evaluation.
• Predictive analytics for social, economic, and environmental policy design.
• Real-time data monitoring for crisis response and disaster risk reduction.
• Big data and citizen-generated data in participatory policy processes.
• Open data ecosystems and transparency in government.
• Data ethics, privacy protection, and algorithmic accountability.

Detailed Themes

Potential focus areas include, but are not limited to:

1. Data-Driven Governance – integrating advanced analytics into policy planning and public sector management.
2. Artificial Intelligence in Policy Design – predictive modeling for economic, environmental, and social policy outcomes.
3. Machine Learning for Public Sector Efficiency – automation, optimization, and resource allocation.
4. Big Data in Social Policy – analyzing large-scale social, demographic, and health datasets for better service delivery.
5. Civic Tech and Digital Democracy – citizen engagement platforms, sentiment analysis, and social media analytics for policy feedback.
6. Geospatial and Remote Sensing Analytics – using GIS and satellite data for urban planning, environmental monitoring, and disaster preparedness.
7. Policy Simulation and Scenario Modeling – agent-based modeling, system dynamics, and computational simulations.
8. Public Health Data Science – pandemic modeling, epidemiological forecasting, and health policy optimization.
9. Environmental and Climate Policy Analytics – carbon tracking, natural resource monitoring, and climate adaptation modeling.
10. Economic Policy and Data Science – trade modeling, labor market forecasting, and fiscal policy simulations.
11. Ethics and Governance of Data – privacy frameworks, data sovereignty, and responsible AI principles.
12. Open Government Data – strategies for improving accessibility, interoperability, and reusability of data.
13. Real-Time Decision Support Systems – early warning systems and crisis management platforms.
14. Social Media and Public Opinion Mining – sentiment tracking for political campaigns and public sentiment analysis.
15. Data Infrastructure for Policymaking – cloud platforms, data warehouses, and interoperability standards.
16. Capacity Building in Data Science for Policy Institutions – training, skills development, and knowledge sharing.
17. Algorithmic Fairness and Bias Mitigation – ensuring equitable outcomes in automated decision-making.
18. Policy Impact Evaluation with Data Science Tools – causal inference, counterfactual analysis, and quasi-experimental designs.
19. Blockchain for Governance – decentralized systems for transparency, procurement, and voting.
20. Interdisciplinary Policy Labs – collaborations between universities, think tanks, and governments for data innovation.

Send your paper to Email: strat.institute@gmail.com