Urban Data Dynamics: A Systematic Benchmarking Framework to Integrate Crowdsourcing and Smart Cities’ Standardization

Vaia Moustaka, Antonios Maitis, Athena Vakali and Leonidas G. Anthopoulos
Additional contact information
Vaia Moustaka: Department of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Antonios Maitis: Department of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Athena Vakali: Department of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Leonidas G. Anthopoulos: Department of Business Administration, University of Thessaly, 41110 Larissa, Greece

Sustainability, 2021, vol. 13, issue 15, 1-43

Abstract: Urbanization and knowledge economy have highly marked the new millennium. Urbanization brings new challenges which can be addressed by the knowledge economy, which opens up scientific and technical innovation opportunities. The enhancement of cities’ intelligence has heavily impacted city transformation and sustainable decision-making based on urban data knowledge extraction. This work is motivated by the strong demand for robust standardization efforts to steer and measure city performance and dynamics, given the growing tendency of conventional cities’ transformation into smart and resilient ones. This paper revises the earlier so-called “cityDNA” framework, which was designed to detect the interrelations between the six smart city dimensions, such that a city’s profile and capacities are recognized in a systematic manner. The updated framework implements the widely accepted smart city (ISO 37120:2018) standard, along with an adaptive Web service, which processes urban data and visualizes the city’s profile to facilitate decision-making. The proposed framework offers a solid benchmarking service, at which the value of crowdsourced data is exploited for the production of urban knowledge and city transformation empowerment. The proposed benchmarking approach is tested and validated through relevant case studies and a proof-of-concept scenario, in which open data and crowdsourced data are exploited. The outcomes revealed that cities should intensify their KPI-driven data production and exploitation along with a set of solid standards for cities to enable cities with customizable scenarios enriched with indicators that reflect each city’s vibrancy.

Keywords: cityDNA; smart cities; crowdsourcing; ISO 37120:2018; city profile (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/15/8553/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/15/8553/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:15:p:8553-:d:605873

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().