Data as Infrastructure for Smart Cities

✍ Scribed by Larissa Suzuki, Anthony Finkelstein

• Publisher: Institution of Engineering and Technology
• Year: 2019
• Tongue: English
• Leaves: 313
• Series: Computing and Networks
• Category: Library

✦ Synopsis

This book describes how smart cities can be designed with data at their heart, moving from a broad vision to a consistent city-wide collaborative configuration of activities. The authors present a comprehensive framework of techniques to help decision makers in cities analyse their business strategies, design data infrastructures to support these activities, understand stakeholders' expectations, and translate this analysis into a competitive strategy for creating a smart city data infrastructure. Readers can take advantage of unprecedented insights into how cities and infrastructures function and be ready to overcome complex challenges. The framework presented in this book has guided the design of several urban platforms in the European Union and the design of the City Data Strategy of the Mayor of London, UK.

✦ Table of Contents

Contents
About the authors
1. Introduction
1.1 Data infrastructure and strategy for smart cities
Part I. Smart cities and data infrastructures
2. The evolution of urban intelligence
2.1 Context
2.1.1 Knowledge and technology innovation in cities
2.2 The evolution of urban intelligence
2.2.1 The digital revolution
2.3 Digital cities
2.3.1 Capabilities development in digital cities
2.3.2 Structural analysis of digital cities
2.4 Ubiquitous cities
2.4.1 Capabilities development in ubiquitous cities
2.4.2 Structural analysis of ubiquitous cities
2.5 Intelligent cities
2.5.1 Capabilities development in intelligent cities
2.5.2 Differentiation factors of intelligent cities
3. Smart cities
3.1 The physical-digital integration of smart cities
3.1.1 The Internet of Things
3.1.2 The city data
3.2 The two categories of smart cities’ applications
3.2.1 Closed-system approaches
3.2.2 Open-systems approach
3.3 Sources of barriers in city data management
4. The management of city data
4.1 Current trends in smart cities data management
4.2 A short introduction to platforms
4.2.1 Network effects
4.2.2 Platform actors and relationships
4.2.3 Platform leadership and governance
4.3 The two prevailing approaches in the provision of city data
4.3.1 Towards a data infrastructure
Part II. The link between data infrastructures and business strategies
5. Services innovation and business models
5.1 Context
5.2 An introduction to business models
5.2.1 e-Business models
5.3 The framework for data infrastructure design
5.3.1 Step 1: Business models outline
5.3.2 Step 2: Evaluation with CSFs
5.3.3 Step 3: Specification of CDIs
5.3.4 Step 4: Closed-loop value-chain model
5.3.5 Step 5: Robustness check
6. The business models framework
6.1 Introduction
6.2 Service design
6.2.1 Comparative advantage of the service innovation
6.2.2 Service’s neutrality, fairness and accountability
6.2.3 Formulating a service strategy
6.3 Technology design
6.3.1 The 9 v’s of city data
6.3.2 Formulating a technology strategy
6.4 Value network design
6.4.1 Data-driven value network
6.4.2 Formulating a value network strategy
6.5 Value design
6.5.1 Formulating a value strategy
6.6 Governance design
6.6.1 Formulating a governance strategy
7. The reference architecture framework
7.1 The logistical distribution of city data
7.2 The forward logistics of city data
7.3 Support activities
7.4 Reverse logistics of city data
7.5 Inside-out and outside-in linkages
7.6 Data infrastructure reference architecture
7.7 Summary
Part III. Applied data infrastructures design
8. Introduction
8.1 Case studies description
8.2 Designing an Open Data Infrastructure
8.2.1 Business models outline
8.2.2 Service design requirements
8.2.3 Technology design requirements
8.2.4 Value design requirements
8.2.5 Governance design requirements
8.2.6 Reference architecture model
8.3 Taking smart cities forward
8.3.1 London Data Infrastructure
8.3.2 Dynamic business models analysis
8.3.3 Business models outline
8.3.4 Service domain requirements
8.3.5 Technology design requirements
8.3.6 Value network design requirements
8.3.7 Value design requirements
8.3.8 Governance domain requirements
8.3.9 Reference architecture model
Part IV. Assessment and evolution of data infrastructure design
9. The dynamics and evolution of business models
9.1 External forces
9.2 Business models evaluation and refinement
9.3 Critical design issues
9.3.1 Service design
9.3.2 Technology design
9.3.3 Value network
9.3.4 Value design
9.3.5 Governance design
9.4 Critical success factors
9.4.1 Providing support to human capability
9.4.2 Providing support to social capability
9.4.3 Providing support to innovation capability
9.4.4 Providing support to institutional capability
9.4.5 Providing support to physical capability
9.4.6 Providing support to sustainable and economic capability
9.5 Summary
10. Applied data infrastructures assessment
10.1 Open data infrastructure case study
10.1.1 Evaluation with CDIs
10.1.2 Evaluation with CSFs
10.1.3 Robustness check
10.2 London Data Infrastructure case study
10.2.1 Evaluation with CDIs
10.2.2 Evaluation with CSFs
10.3 Complementary tools and techniques
10.3.1 Volumetric analysis of city data
10.3.2 Simulation of CDIs
11. Conclusion
References
Index