Building trustworthy smart cities: The concept definition of the smart metrology campus data infrastructure

Abstract

This article highlights the need for a robust data infrastructure as the foundation for data-driven smart cities. It presents a guideline for developing such infrastructure, emphasizing a holistic analysis of the problem, stakeholder requirements, and long-term considerations like maintenance and system end-of-life. The Smart Metrology Campus concept aims to enable reliable data science in smart cities by integrating sensor and meter data with metrology-based metadata. Previous research identified systems engineering, specifically the ISO 12588 standard, as the optimal approach for building this infrastructure. This article applies the first half of this approach to a case study: the acquisition and historicization of electricity data and metadata for energy efficiency research. The process begins with concept definition, analyzing the use case context, stakeholder requirements, and system lifecycle phases. These insights help determine the most suitable data management system (e.g., data warehouse or data lake). The article explores methods from model-based systems engineering (MBSE) and requirement engineering for efficient concept definition, applying them to the Smart Metrology Campus case. The study concludes that a lambda architecture, a big data framework, is the ideal foundation for realizing the Smart Metrology Campus.