A Flexible Architecture for Key Performance Indicators Assessment in Smart Cities

Sanctis, Martina De; Iovino, Ludovico; Rossi, Maria Teresa; Wimmer, Manuel

doi:10.1007/978-3-030-58923-3_8

Cited by 7 publications

(12 citation statements)

References 20 publications

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“…The given modeling approach allows designers to select relevant KPIs for the candidate smart cities, thus to enable a customization of the measured KPIs. This can be done through a dedicated editor as envisioned in [17], where we planned a KPIs Fragment Selection/Customization Editor. This editor will allow users to "query" the KPIs definition model to select and possibly customize given KPI definitions and generate model fragments [29].…”

Section: Supporting Evolutionary Kpismentioning

confidence: 99%

“…The presented approach builds on top of previous work. In [17], we presented the flexible architecture of the tool, identifying both required and optional components and functionalities needed for realizing the automatic KPIs assessment. We also showed flexibility points allowing for different specification of the architecture (e.g., standalone, hybrid, online) through diverse technologies.…”

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confidence: 99%

“…The extensions of this work w.r.t. [17,18] are manifold. Firstly, we show how the evaluation engine has been implemented with a complete model-based approach; moreover, we show a new extension of our framework that exploits model-driven dashboards devoted to the visualization of the KPIs model once it is actualized with the results of the evaluation.…”

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confidence: 99%

“…Secondly, we further improved the scalability of our evaluation engine w.r.t. [17], by performing relevant code refactoring in the framework that reduced the computation time about 50%. We evaluated the approach with several smart cities also varying the KPIs definition in order to see how the framework implementation scales with real-world exemplary models.…”

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confidence: 99%

“…The results are positive and encourage to further improve the presented approach with a self-contained tool support. The process, methodology, and the components treated in this paper are core of the assessment process and they are needed to enable the architectural framework described in [17].…”

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confidence: 99%

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MIKADO: a smart city KPIs assessment modeling framework

et al. 2021

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Smart decision making plays a central role for smart city governance. It exploits data analytics approaches applied to collected data, for supporting smart cities stakeholders in understanding and effectively managing a smart city. Smart governance is performed through the management of key performance indicators (KPIs), reflecting the degree of smartness and sustainability of smart cities. Even though KPIs are gaining relevance, e.g., at European level, the existing tools for their calculation are still limited. They mainly consist in dashboards and online spreadsheets that are rigid, thus making the KPIs evolution and customization a tedious and error-prone process. In this paper, we exploit model-driven engineering (MDE) techniques, through metamodel-based domain-specific languages (DSLs), to build a framework called MIKADO for the automatic assessment of KPIs over smart cities. In particular, the approach provides support for both: (i) domain experts, by the definition of a textual DSL for an intuitive KPIs modeling process and (ii) smart cities stakeholders, by the definition of graphical editors for smart cities modeling. Moreover, dynamic dashboards are generated to support an intuitive visualization and interpretation of the KPIs assessed by our KPIs evaluation engine. We provide evaluation results by showing a demonstration case as well as studying the scalability of the KPIs evaluation engine and the general usability of the approach with encouraging results. Moreover, the approach is open and extensible to further manage comparison among smart cities, simulations, and KPIs interrelations.

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Section: Supporting Evolutionary Kpismentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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MIKADO: a smart city KPIs assessment modeling framework

et al. 2021

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Weaving Open Services with Runtime Models for Continuous Smart Cities KPIs Assessment

Sanctis

Iovino

Rossi

et al. 2021

Service-Oriented Computing

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Responsible innovation assessment tools: a systematic review and research agenda

Guimarães

Amorim

Almeida

2022

TECHS

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PurposeResponsible innovation assessment tools (RIATs) are key instruments that can help organizations, associations and individuals measure responsible innovation. Accordingly, this study aims to review the current status of research on responsible innovation and, in particular, of studies that either present the relevance of RIATs or provide empirical evidence of their adoption.Design/methodology/approachA systematic literature review is conducted to identify and review how RIATs are being addressed in academic research and the applications that are proposed. A systematic process is implemented using the Web of Science and Scopus bibliographic databases, aiming not only to summarize existing studies, but also to include a perspective on gaps and future research.FindingsA total of 119 publications were identified and included in the review process. The study identifies that RIATs have attracted growing interest from the scientific community, with a greater predominance of studies involving qualitative and mixed methods. A well-balanced mix of conceptual and exploratory studies is also registered, with a greater predominance of analysis of RIATs application domains in the past years, with greater incidence in the finance, water, energy, construction, manufacturing and health sectors.Originality/valueThis study is pioneering in identifying 16 dimensions and 60 sub-dimensions for measuring responsible innovation. It also suggests the need to include multidimensional perspectives and individuals with interdisciplinary competencies in this process.

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A Flexible Architecture for Key Performance Indicators Assessment in Smart Cities

Cited by 7 publications

References 20 publications

MIKADO: a smart city KPIs assessment modeling framework

MIKADO: a smart city KPIs assessment modeling framework

Weaving Open Services with Runtime Models for Continuous Smart Cities KPIs Assessment

Responsible innovation assessment tools: a systematic review and research agenda

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