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Implementing Data-Driven Strategies in Smart Cities

  • ID: 5230532
  • Book
  • August 2021
  • 216 Pages
  • Elsevier Science and Technology

Implementing Data-Driven Strategies in Smart Cities is a guidebook and roadmap for practitioners seeking to operationalize data-driven urban interventions. The book examines the revolution that big data, data science, and the Internet of Things are making feasible for cities, then explores alternate topologies, typologies, and approaches to operationalize data science in cities-all drawn from global examples, including top-down, bottom-up, greenfield, brownfield, issue-based, and data-driven. The guide channels and expands on the classic data science model for data-driven interventions in cities-data capture, data quality, cleansing and curation, data analysis, visualization and modeling, and data governance, privacy and confidentiality.

Throughout, illustrative case studies demonstrate successes realized in such diverse cities as Helsinki, Nice, Tartu, San Cugat, Singapore, Sao Paolo, Bilbao, and Goyang City. Given the heavy emphasis on global case studies, this work is particularly suitable for any urban manager, policymaker, or practitioner responsible for delivering technological services for the public sector, from sectors as diverse as energy, transport, pollution, and waste management.

  • Explores numerous specific urban interventions drawn from global case studies, helping readers understand real urban challenges and create data-driven solutions
  • Provides a step-by-step and applied holistic guide and methodology for immediate application of your own business agenda
  • Presents cutting edge technology including innovations such as blockchain, artificial intelligence, and digital twins
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1. Introduction
2. Governance, Decision Making and Strategy for Smart Cities
3. Data Science for Smart Cities
4. Roadmap to Develop a Data-Driven City
5. Data Capturing, Cleaning and Curation in Smart Cities
6. Data Analysis, Modelling and Visualization in Smart Cities
7. Data Governance, Privacy and Confidentiality in Smart Cities
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Grimaldi, Didier
Dr. Didier Grimaldi is Associate Professor at the La Salle - Ramon Llull University, Spain. His scholarly interests span over novel forms of innovation to develop new or existing businesses analyzing different models of public-private governance which offer a more active role to the citizens. His research focuses on evaluating the real impact of the emerging technologies (Big Data, Internet of Things, Drones, Social Media, etc.) to promote new services for the citizens and improving their quality of life. He received his Ph.D. studying the role of the different actors of the innovation quadruple helix model (Private, Public, University and Citizen) in the development of the smart city.
Carrasco, Carlos
Carlos Carrasco is a researcher and data scientist at IESE Business School. Previously, he carried out a MRes in Management Sciences at ESADE Business School and a MSc in Public and Social Policy at Pompeu Fabra University and Johns Hopkins University. Additionally, he studied public finance at the London School of Economics & Political Science and government performance at Harvard University. He has worked in public sector consulting for the Barcelona Provincial Council and is founder and Chief Data Scientist at EIXOS, a company dedicated to the creation of urban economic observatories based on Big Data and geospatial technologies. He has also contributed to various academic and non-academic publications and books on economics, management and urban strategy.
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