Smart places, such as the dematerialization of diverse natural ecosystems, involve several autonomous ecosystems that interconnect and promote the integration of information and the convergence of necessarily secure functions and activities that depend on reliable data and sources. The problem of data management, quality, and governance is aggravated by the amount of data generated, the multiplicity of devices, spaces, infrastructures, users, and connected entities, being a technological and management challenge. The various cyber risks can lead to data compromise, exploitation of weaknesses, infiltration of systems, conditioning the functioning of the city, and, to the limit, disengaging or even destroying the physical infrastructure to the point where citizens have their lives threatened.
The research methodology chosen for this work is the Design Science Research (DSR) methodology, in the problem-centered approach, where we intend to construct an artifact, which allows us to evaluate viable alternatives for using reliable, blockchain-based technology.
The proposal focuses on a generic data model to be applied to smart places in the context of smart cities, focusing on their revision and structuring in data management aspects and governance. The proposed model adopts blockchain technologies and applies to the different characteristics of the city, in the electronic governance, in the contracting of products and services, and in the collection of data. Various IoT objects and multiple networks, along with blockchain technology, can result in safer and more efficient spaces and cities. This work explores the concept of smart cities in the mobility and transport ecosystem, using blockchain technology as a platform for data security and reliability, applied in the ticketing subsystem and traffic subsystem, for the safety and control of the logs generated by the numerous devices.
With this artifact it is intended the generalization of the model be applied to different subsystems allowed that generic data models, be integrated and automated, with quality data and reliable information. Controlling data flows, and managing the data and information lifecycle will enable a more reliable data management, information management, and governance process.