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A Flexible Architecture for Key Performance Indicators Assessment in Smart Cities

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Book cover Software Architecture (ECSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12292))

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Abstract

The concept of smart and sustainable city has been on the agenda for the last decade. Smart governance is about the use of innovation for supporting enhanced decision making and planning to make a city smart, by leveraging on Key Performance Indicators (KPIs) as procedural tools. However, developing processes and instruments able to evaluate smart cities is still a challenging task, due to the rigidity showed by the existing frameworks in the definition of KPIs and modeling of the subjects to be evaluated. Web-based platforms, spreadsheets or even Cloud-based applications offer limited flexibility, if the stakeholder is interested not only in using but also in defining the pieces of the puzzle to be composed. In this paper we present a flexible architecture supporting a model-driven approach for the KPIs assessment in smart cities. It identifies both required and optional components and functionalities needed for realizing the automatic KPIs assessment, while showing flexibility points allowing for different specification of the architecture, thus of the overall methodology.

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Notes

  1. 1.

    https://sustainabledevelopment.un.org/sdgs.

  2. 2.

    Key Performance Indicators in Power Pivot at https://bit.ly/37EFR9r.

  3. 3.

    Project available at: https://github.com/gssi/SmartCityModeling.git.

  4. 4.

    https://www.eclipse.org/modeling/emf/.

  5. 5.

    https://www.eclipse.org/acceleo/.

  6. 6.

    For the interested readers it can be found at https://bit.ly/3bqbqG2.

  7. 7.

    https://theia-ide.org.

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Acknowledgment

This work was partially supported by the Centre for Urban Informatics and Modelling, National Project, GSSI as well as by the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development.

Author information

Authors and Affiliations

  1. Gran Sasso Science Institute, L’Aquila, Italy

    Martina De Sanctis, Ludovico Iovino & Maria Teresa Rossi

  2. CDL-MINT, Johannes Kepler University, Linz, Austria

    Manuel Wimmer

Authors
  1. Martina De Sanctis
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  2. Ludovico Iovino
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  3. Maria Teresa Rossi
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  4. Manuel Wimmer
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Corresponding author

Correspondence to Martina De Sanctis .

Editor information

Editors and Affiliations

  1. Koninklijke Philips N.V., Eindhoven, The Netherlands

    Anton Jansen

  2. VU Amsterdam, Amsterdam, The Netherlands

    Ivano Malavolta

  3. University of L’Aquila, L’Aquila, Italy

    Henry Muccini

  4. Carnegie Mellon University, Pittsburg, PA, USA

    Ipek Ozkaya

  5. University of Applied Sciences of Eastern Switzerland, Rapperswil, Switzerland

    Olaf Zimmermann

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De Sanctis, M., Iovino, L., Rossi, M.T., Wimmer, M. (2020). A Flexible Architecture for Key Performance Indicators Assessment in Smart Cities. In: Jansen, A., Malavolta, I., Muccini, H., Ozkaya, I., Zimmermann, O. (eds) Software Architecture. ECSA 2020. Lecture Notes in Computer Science(), vol 12292. Springer, Cham. https://doi.org/10.1007/978-3-030-58923-3_8

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  • DOI: https://doi.org/10.1007/978-3-030-58923-3_8

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  • Online ISBN: 978-3-030-58923-3

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