There is some consensus among researchers that the first urban civilization labeled a 'city' was Sumer in the period 3,500-3,000 BC. The meaning of the word, however, has evolved with the advancement of technology. Adjectives such as digital, intelligent, and smart have been prefixed to 'city', to reflect the evolution. In this study, we pose the question: What makes a 'Smart City', as opposed to a traditional one? We review and synthesize multiple scientific studies and definitions, and present a unified definition of Smart City-a complex concept. We present the definition as an ontology which encapsulates the combinatorial complexity of the concept. It systematically and systemically synthesizes, and looks beyond, the various paths by which theory and practice contribute to the development and understanding of a smart city. The definition can be used to articulate the components of a Smart City using structured natural English. It serves as a multidisciplinary lens to study the topic drawing upon concepts from Urban Design, Information Technology, Public Policy, and the Social Sciences. It can be used to systematically map the state-of-the-research and the state-of-the-practice on Smart Cities, discover the gaps in each and between the two, and formulate a strategy to bridge the gaps.
We present ontological meta-analysis and synthesis as a method for reviewing, mapping, and visualizing the research literature in a domain cumulatively, logically, systematically, and systemically. The method highlights a domain's bright spots that have been heavily studied, the light spots that have been lightly studied, the blind spots that have been overlooked, and the blank spots that have not been studied. It highlights the biases in a domain's research; the research can then be realigned to make it stronger and more effective. We illustrate the method using the emerging domain of public health informatics (PHI). We present an ontological framework for the domain, map the literature onto the framework, and highlight its bright, light, and blind/blank spots. We also present detailed analyses using the ontological maps of dyads and triads. We conclude by discussing how (a) the results can be used to realign PHI research, and (b) the method can be used in other information systems domains.
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