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Conclusion

Conclusion

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This book concentrates on the definition of data infrastructures and their business models and components. The method employs a business model-driven approach to support the elicitation and modelling of requirements and data strategies, and a closed-loop supply chain model to serve as a reference architecture model for data infrastructures. By using critical design issues and factors, the positive and negative contributions that may occur among the requirements and specific design needs can be easily identified, as well as the final contributions of the data infrastructure to the realisation of smart cities. Our framework facilitates the requirements of elicitation process from business models analysis, and the detection of requirements mismatches across the five domains of the business models. It offers templates for requirements balancing and refinement which can be used to determine the trade-offs to be made during the design of such large interconnected systems. The dynamic business models' approach enables decision-makers to evaluate the evolution of the business models and how external factors may impact the several stages of the development process of digital strategies of cities. The closed-loop supply chain model can give government and their value network of partners the ability to better collaborate on the basis of a common and accurate reference architecture. As such, cities are equipped with methodologies that facilitate the design and delivery of sustainable, agile, evolvable and cost-effective data management solutions for smart cities.

Chapter Contents:

  • 11 Conclusion

Inspec keywords: government policies; supply chain management; Big Data; systems analysis; business data processing; standards; sustainable development; smart cities

Other keywords: sustainable data management; data strategies; critical design issues; large interconnected systems; business model-driven approach; business models analysis; closed-loop supply chain model; data infrastructures; requirements elicitation; requirements balancing; digital strategies; dynamic business models; government; reference architecture model; cost-effective data management solutions

Subjects: Data handling techniques; Business and administration; Economic, social and political aspects of computing

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