The way cities and wider urban systems are understood depends, to a certain extent, on the data available. Limited data sources and analytical capabilities of computational systems in previous decades allowed for equally bounded insights into how cities work.
With our modern-day cities come vast quantities and new forms of data that reflect how people interact with the urban environment and with each other. And as urban data sources and technologies are rapidly expanding into new corners of our everyday experience, urban planning and policy-making are also undergoing a revolution. This trend gives rise to questions like:
How can urban data redefine the way we understand cities, and offer new avenues to planning and governance? And what are corresponding challenges?
Data-driven approaches and smart cities
At this year’s SmartCity International Symposium, organized by The College of Urban Science at Incheon National University in Korea, international experts in the field of smart cities from 9 different countries were invited to share research results and to reinforce academic exchange and competencies in the field.
Here, our Research Fellow Dr. Achilleas Psyllidis hosted a keynote speech on “data-driven approaches to understanding and planning smart cities”.
Data to better understand, plan and govern city dynamics
At AMS Institute, Psyllidis leads the Social Urban Data Lab (SUDL), which works at the leading edge of urban analytics to make sense of these data and to maximize their value. During his keynote, he focused on future-forward computational approaches, methods, and tools that facilitate a better understanding of city dynamics and inform urban planning and policy-making.
Our Research Fellow illustrated a prominent example of his work: SocialGlass. This online system harnesses urban big data to help city stakeholders better understand and forecast city dynamics. Furthermore, Psyllidis addressed various application domains relating to cities, and showcased examples around the topics of human activity dynamics, smart mobility, location optimization, and smart identification of urban objects.
He emphasized that combining multiple data sources could help mitigate the inherent limitations of each source and, thereby, resolve many of the drawbacks present in individual datasets
“The way cities and wider urban systems are understood depends, to a certain extent, on the data available. As urban data sources and technologies are rapidly expanding into new corners of our everyday experience, urban planning and policy-making are also undergoing a revolution.”
Solutions resulting from Urban Data Science
By valorizing cross-domain expertise in data science, the Urban Data Science team contributes to the AMS Solutions Portfolio, and offers AMS researchers and partners state-of-the-art technological and methodological solutions for urban data creation, integration, enrichment, analysis, and exploration.
Would you like to learn how to extract meaningful information from urban data? During our 4-day Urban Data Science course you'll adopt new skills to find solutions for city challenges. For more Urban Data related information:
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