Larissa Romualdo Suzuki.

PhD in Software Systems Engineering and Smart Cities

Welcome to my academic website. Here you can find a bit of information on my Ph.D. Thesis. If you want to learn more about my work please visit Here.

Ph.D. Thesis Abstract

DATA AS INFRASTRUCTURE FOR SMART CITIES Suzuki, L. C. D. S. R. (2015). PhD Thesis, University College London.

The systems that operate the infrastructure of cities have evolved in a fragmented fashion across several generations of technology, causing city utilities and services to operate sub-optimally and limiting the creation of new value-added services. The integration of cross-domain city data offers a new wave of opportunities to mitigate some of these impacts and enables city systems to draw effectively on interoperable data that will be used to deliver smarter cities.

Despite the considerable potential of city data, current smart cities initiatives have mainly addressed the problem of data management from a technology perspective, have treated it as a single and disjoint ICT development project, and have disregarded stakeholders and data needs. As a consequence, such initiatives are susceptible to failure from inadequate stakeholder input, requirements neglecting, and information fragmentation and overload.

We argue that through more deliberate orchestration of open and proprietary data provided by both public and private sectors, and through addressing privacy and trust issues in relation to volunteered citizen data, we can transform existing disjoint data repositories into data infrastructures and marketplaces ready for the data explosion that the Internet of Things and the systems of systems integration will produce.

This thesis defines data infrastructure as “the basic physical, digital, organisational and governance structures and processes needed for the management of all data that underpins the decision making processes in smart cities”.

To enter into the new era of data exploitation and data infrastructures cities will need to adopt a more strategic and outcomes-oriented approach and this research is about this journey. This thesis proposes a systematic business-model-driven framework, named SMARTify, to guide the design of large and highly interconnected data infrastructures which are provided and supported by multiple stakeholders. The framework is used to model, elicit and reason about the requirements of the service, technology, organization, value, and governance aspects of smart cities. The requirements serve as an input to a closed-loop supply chain model, which is designed and managed to explicitly consider the activities and processes that enables the stakeholders of smart cities to efficiently leverage their collective knowledge.

We demonstrate how our approach can be used to design data infrastructures by examining the degree to which the results of the SMARTify approach handles the holistic design of a data infrastructure and informs the decision making process. To establish the effectiveness of SMARTify to improve the quality of data infrastructures design, we have validated the framework against real-world case studies in different domains using a combination of both real systems and software simulation.

The case studies have shown that the SMARTify framework support data infrastructure design process by facilitating cross-domain data exploitation, the emergence of new profitable business models, and the development of an increase range of new and engaging services in smart cities. It also provides cities with the clarity they need to think strategically about how systems, businesses and interested citizens can draw effectively on a vast supply of cross-domain city data through a data infrastructure.

We feel privileged that the case study and concepts of this thesis created the Data For London - A City Data Strategy for the Greater London Authority, and to drive the requirements elicitation of urban platforms for the European Innovation Partnership projects (Urban Platforms).

Data infrastructures can provide many functionalities that transcend space (and time), break down the barriers to information access and enhance communication and collaboration among government, businesses and citizens. As a result, it enables stakeholders of city data to have access to information that will enable them to innovate, to work better, to commute more efficiently in between places, enable governments to get insights on the urban services being provided anywhere and anytime they want.

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Data as Infrastructure for Smart Cities

Citing This Work

Reference: "Data as Infrastructure for Smart Cities", Suzuki, LCSR, 2015, University College London, PhD Thesis.

Author: Dr Larissa Romualdo-Suzuki

Position: Researcher

Affiliation: UCL, Department of Computer Science / Imperial College Business School, Digital City Exchange Program.

Funding bodies: EPSRC, Google and Intel

Acknowledgements: The authors want to thanks ARUP for providing us with a real world case study, and the Greater London Authority for the feedback received during the development of the London case study.


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Contact details: larissa.romualdo.11@ucl.ac.uk