The I International Conference on Public Policies and Data Science is a collaborative effort between the Federal University of Amazonas and the University of Aveiro (Portugal), which has the support of the Government of Amazonas (Brazil). It aims at reflecting on the challenges of decision-making in public policies and the role of data science in enhancing the design, implementation and evaluation of these policies. The conference objectives are to emphasize the critical role of technical and  data-informed decision-making, using integrated methods that gather and analyze information from multiple sources, resulting in more informed, participated, inclusive, transparent, and consistent public policy outcomes. The conference endeavors to i) encourage the debate and exchange of experiences on relevant areas of research and innovation; and ii) create an environment to address the challenges and opportunities posed by the increasing volume of accessible data  and the improved computational and technological capacity that characterize the present times. By drawing attention to the importance of evidence-based decision-making, the conference aims to enhance the quality of public policy and respond effectively to societal challenges.


Furthermore, this is coordinated with the organisation of the II Conference on Data Science for the Social Sciences. The conference embraces an international and interdisciplinary outlook, fostering scientific and technological exchange and dissemination of knowledge among researchers from diverse countries, academic disciplines, and scales of action. This unique gathering will provide a platform for researchers to share their expertise and exchange ideas.


In order to stimulate the debate around the social, economic, environmental and territorial dimensions that shape the current territorial context, and to promote interdisciplinary collaboration for informed decision-making, the following central themes are defined:


  • Natural environment, resources and rural development
  • Smart and Sustainable Cities
  • Open Data and Big Data 
  • Data Mining
  • Deep learning
  • Sustainable Urban and Regional Development
  • Sport and regional development
  • Energy and environmental economics
  • Education and health
  • Governance and public policy
  • Housing, rehabilitation and real estate
  • Infrastructure, transport and accessibility
  • Social innovation, integration, poverty and exclusion
  • Artificial Intelligence
  • Machine Learning
  • Mitigation and adaptation to climate change
  • Models and Methods in Regional Science
  • Population, migration and labour market
  • Regional Resilience and Crisis
  • Decision Support Systems 
  • Geographical Information Systems and location models
  • Tourism and Culture 
  • Data Visualisation


Academics and researchers, professionals, technicians who have worked and are interested in the themes of Regional Development/Public Policies and Data Science/Decision Support Systems are invited to submit their papers.


Papers by track