Table 7 Topics related to the knowledge gaps in the area of data-driven smart eco-cities

• Conceptual and theoretical models for data-driven smart eco-cities

• Analytical frameworks for data-driven smart eco-cities as to three sustainability dimensions

• Assessment methods for evaluating data-driven smart eco-city development at different spatial scales

• Eco-cities and science fiction and utopian discourses

• Socially responsible urban intelligence for eco-urbanism

• Data-driven smart solutions for environmental sustainability

• The economic, social, cultural, political, institutional, and ethical dimensions shaping data-driven smart eco-cities

• Opportunities and challenges for engineering and developing new build data-driven smart eco-cities

• Socio-technical and transformative approaches to data-driven smart eco-city governance

• Balancing techno-centric and human-centric policies in data-driven smart eco-city development

• Eco-social policy integration in the practice of emerging data-driven smart eco-cities

• Political ecology of data-driven smart eco-cities

• Comprehensive models for integrating eco-city design strategies and smart city technology solutions

• Urban intelligence functions for monitoring and developing data-driven smart eco-cities

• Horizontal information platforms and operations centers for data-driven smart eco-cities

• Big data-enabled frameworks and architectures for data-driven smart eco-cities

• The risks and implications of sensorization, hyper-connectivity, and algorithmization on residents

• The negative implications of digitally instrumenting the built environment of eco-cities

• Advanced simulation models for dealing with new conceptions of data-driven smart eco-cities as dynamically changing urban environments and self-organizing social networks

• Simulation models and optimization methods based on the integration of complexity science and sustainability science for optimal designs for improving ecological sustainability

• Models of data-driven smart eco-cities functioning in real-time

• New smart eco-urbanism theories based on data-intensive science

• Data-driven long-term, short-term, and joined-up planning for eco-city projects

• Integrating passive solar, low-energy, and net-zero houses/buildings with smart energy technologies

• Data-driven smart approaches to strategic planning of building energy retrofitting

• Modeling and simulation of SIDs

• Data-driven smart climate change mitigation and adaptation strategies

• Digital ecosystems for smart eco-cities (smart environments, intelligent systems, distributed systems, data management)

• Data-sharing in smart eco-cities (data markets, data governance, privacy and security preserving technologies, data engineering, distributed ledger technologies, ontologies/taxonomies)

• Data-driven citizen-centered service innovation in smart eco-cities (public services, mobility, sharing economy)

• Resilient data-driven smart eco-cities (cyber security, situation awareness, emergency preparedness, intelligent city infrastructure)

• Accelerating renewable energy transitions in data-driven smart eco-cities

• The pace of the diffusion of zero-emission innovations in data-driven smart eco-cities

• Influence of policy discourse networks on local renewable energy transitions in smart eco-cities

• Challenges and barriers to the upscaling and diffusion of environmental innovations in data-driven smart eco-cities

• The impact of data-driven smart technologies on the pace of renewable energy transitions in eco-cities

• The impacts of evidence-based policy decisions on the pace of environmental innovations in eco-cities

• Best practices for the rapid diffusion of environmental innovations in data-driven smart eco-cities