Overview
Cities today generate unprecedented volumes of data from a variety of sources, including transport systems and utilities, environmental monitoring, and citizen services. The surge in information holds transformative potential for making urban environments more efficient, sustainable and resilient.
The 3-day Urban Data Management Programme will equip participants with the knowledge and practical skills needed to manage urban data for smart city applications, making urban environments more efficient, sustainable and resilient.
What you can expect to learn
The course addresses the collaboration challenges involved in bridging gaps between public servants, who may lack urban data expertise, and statisticians, who are not always familiar with city administration.
By the end of this programme, participants will be able to:
- Understand the fundamentals of urban data and its role in smart city ecosystems.
- Navigate key issues in data governance, privacy, and ethical considerations.
- Apply data-driven approaches to urban planning, decision-making, and service delivery.
- Evaluate existing smart city initiatives through case study analysis.
- Understand how to integrate AI, machine learning, and IoT into urban analytics and services.
- Champion evidence-based, inclusive, and transparent policy development.
- Recognize challenges and barriers to implementation and anticipate future urban innovation trends.
- Safeguard data ethics, privacy and security in urban data use
- Collaborate across disciplines and sectors
- Evaluate impacts of data initiatives on sustainability and resilience
- Learn how to establish joint data teams (statisticians, municipal analysts, policymakers) to ensure effective collaboration and data driven decision making
- Next Course Starts On 10 March 2026See Full Schedule
- Duration10, 11, 12 March 2026 (3 days)
- LevelIntermediate
- VenueSingapore Management University
Learning Objectives
- Examine the broader relevance of urban data management, particularly how it can contribute to the achievement of Sustainable Development Goals (SDGs)
- Learn to offer a transferable framework for cities seeking to strengthen evidence-based policymaking.
- Design, implement, and evaluate data-driven urban initiatives that genuinely improve systems whilst maintaining standards of data privacy and protection.
Topics/Structure
- Why data is important to smart cities, and what good data management looks like
- Overview of different types of urban data: infrastructure, mobility, utilities, environment, social services; and of different data ecosystems: public, private, citizen-generated
- Overview of smart cities and how they use data to transform urban landscapes in an environmentally, economically, and socially responsible way
- How the challenges of big data governance such as discrimination, cyberthreats or loss of privacy highlight the need to establish a regulatory framework.
- Introduce global data ecosystems and governance models relating to urban data
- Data governance foundational principles: privacy, quality, security
- Smart city development frameworks and best practices
- Standards and benchmarks for smart city development
- Transparency, accountability, and citizen participation in governance
- Ethical and cultural considerations: data protection, balancing innovation with societal values
- Strategies for engaging local communities
- Introduction to ISO 37120/37130 Smart City Certification (WCCD), and related UN initiatives including U4SSC (ITU, UNECE, UN-Habitat) and UN Habitat’s Voluntary Local Reviews (VLR)
- Using data-driven decision making in mobility, resource management, and planning
- Ensuring methodological consistency across municipalities so that local figures remain comparable nationally and internationally, safeguarding against “data silos”
- Using insights from urban data to design integrated social policies
- Importance of cybersecurity in protecting critical infrastructure and citizen data
- Strategies for syncing up national data with urban applications (e.g., linking social services data with housing or demographic registers)
- Syncing national statistics and datasets with municipal applications
- Bridging official statistics and local governance to enhance decision-making
- Creating actionable urban intelligence from integrated datasets
- AI and machine learning in urban analytics, planning, and service optimisation
- Using predictive modelling of urban phenomena, such as anticipating energy demand peaks or monitoring environmental quality
- Integrating big data sources (city-wide sensors, telecom data) with official statistics
- Anticipating trajectories of urban innovation for the next decade
- Explore predictive analytics and IoT
- Conduct a hands-on workshop to design/ evaluate an initiative
- Case studies of successful and unsuccessful projects
- Designing KPIs and impact assessment tools for smart city initiatives
- Funding models and governance innovations for implementation
- Understanding challenges and barriers: financial, regulatory, and technical
Who Should Attend
- City officials and policymakers shaping digital urban strategies
- Urban planners and project managers of smart cities
- Technology executives and consultants involved in government services
- Researchers interested in the practical side of urban innovation and governance
- Data specialists and statisticians seeking urban governance context
- NGOs and international development agencies engaged in urban innovation
- Professionals working on sustainable urban development, resilience and technology-driven city projects
Takeaways
Applied orientation:
➤ Focuses on practical case studies, tools, and frameworks used in real-world smart city projects.
Experiential learning:
➤ Includes curated site visits to see concepts in action. Potential site visits include
- Smart Nation Cityscape Exhibition at Singapore's Urban Redevelopment
Authority - Punggol Digital District Open Digital Platform (ODP)
- Singapore's Land Transport Authority SG Mobility Gallery
- The Innovation Centre by PSA Singapore, formerly known as "Port of Singapore Authority"
- Singapore Land Authority GeoWorks Office
Interdisciplinary foundation:
➤ Combines urban studies, data science, governance, and technology.
Forward-looking:
➤ Anticipates future trends in AI, IoT, and data ethics in urban contexts.
Global and local relevance:
➤ Connects international smart city benchmarks with local policy and community engagement.
Fees and Funding
SGD 4,350
(inclusive of 9% GST)*
SGD 4,000
(excluding 9% GST)*
* Fee is subject to change. GST applies to individuals and Singapore-registered companies.
* For Singaporeans aged 25 and above, you may utlise your SkillsFuture Credits to defray part of the programme fee.
Please refer to SkillsFuture Singapore's SkillsFuture Credit page for more details.
** Fee is subject to change. GST is not applicable to foreign based companies.
For More Information:
Tel: +65 6826 1317 (Ayden Tay)
Email: aydentay@smu.edu.sg
Schedule
Start Date(s):
Intake Information :26, 27, 28 Jan 2026 (3 days)
