Semantic-enhanced living labs for better interoperability of smart cities solutions

Villanueva-Rosales, Natalia; Chavira, Luis Garnica; Larios, Victor M.; Gomez, Leopoldo; Aceves, Emmanuel

doi:10.1109/isc2.2016.7580775

Cited by 16 publications

(7 citation statements)

References 3 publications

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“…However, the democratization of science [16] and innovation [17], or the shift towards a more equitable engagement between experts and the lay public, are clear virtues of both approaches. Further, in the creation of a Smart City vision, the synergy of both approaches appears beneficial [18]: CS can help in developing and accumulating the skills of citizens (e.g., [19,20]), while ULLs can help in the ability of sharing and exchanging data and services across different urban platforms (e.g., [21,22]).…”

Section: Introductionmentioning

confidence: 99%

Urban Living Labs and Citizen Science: From Innovation and Science towards Policy Impacts

Veeckman

Temmerman

2021

Sustainability

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City governments are currently exploring different participatory mechanisms in order to meet the growing demand in society for deliberate decision-making. Through developments in sensing technology, data processing and visualization, citizen science is emerging as a powerful tool for the general public to participate in scientific research that informs policy. Citizen science can be used as an approach in Urban Living Labs, whereby public and private stakeholders are involved in innovation and data collection processes together with citizens. However, there is currently little synergy between citizen science and Urban Living Labs, and how science, innovation and policy can be interoperable. Therefore, this article conducts a comparative case study analysis on the participatory processes and related outputs, outcomes and impacts of the FloodCitiSense Urban Living Labs (Brussels, Birmingham, Rotterdam). These initiatives developed an early warning system for urban flooding through the collection and analysis of crowdsourced information. Data on the participatory processes were collected through 11 in-depth interviews and evaluated on its effectiveness in achieving policy outcomes. The discussion reflects on best practices in incorporating citizen science in Urban Living Labs based on the experienced opportunities and challenges in FloodCitiSense.

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Section: Introductionmentioning

confidence: 99%

Urban Living Labs and Citizen Science: From Innovation and Science towards Policy Impacts

Veeckman

Temmerman

2021

Sustainability

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“…Smart cities are complex ecosystems in which many distinct aspects coexist, and many kinds of actors interact. Living Labs (LL) are instruments for the development and implementation of technology to accelerate innovation in cities (Villanueva-Rosales et al 2016;Coenen et al 2014). A LL is a starting point to collaborate on and generate models to create smart cities (Cosgrave et al 2013;Majeed et al 2017;Concilio 2016), i.e., it is a way to develop collaborative systems to engage the community/stakeholders (e.g., students, lecturers, computer scientists, electronics engineers, politician and tourists).…”

Section: Adoption Processmentioning

confidence: 99%

“…To realize a SCCR, it is necessary to understand: (i) the SCCR requirements; (ii) data sources needed to monitor the scenarios; and (iii) services the decision makers want to provide to various categories of users. One of the key aspects consists of establishing relationships that define guidelines and common operating modes with all the stakeholders and operators who have to work together to create/manage the dashboard (DeMarco et al 2015;McArdle et al (2016); Suakanto et al 2013). In this regard, it is of fundamental help to use collaborative tools such as the Living Lab support on Web portals.…”

Section: Introductionmentioning

confidence: 99%

Snap4City Platform to Speed Up Policies

Mitolo

Nesi

Pantaleo

et al. 2021

Smart and Sustainable Planning for Cities and Regions

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In the development of smart cities, there is a great emphasis on setting up so-called Smart City Control Rooms, SCCR. This paper presents Snap4City as a big data smart city platform to support the city decision makers by means of SCCR dashboards and tools reporting in real time the status of several of a city’s aspects. The solution has been adopted in European cities such as Antwerp, Florence, Lonato del Garda, Pisa, Santiago, etc., and it is capable of covering extended geographical areas around the cities themselves: Belgium, Finland, Tuscany, Sardinia, etc. In this paper, a major use case is analyzed describing the workflow followed, the methodologies adopted and the SCCR as the starting point to reproduce the same results in other smart cities, industries, research centers, etc. A Living Lab working modality is promoted and organized to enhance the collaboration among municipalities and public administration, stakeholders, research centers and the citizens themselves. The Snap4City platform has been realized respecting the European Data Protection Regulation (GDPR), and it is capable of processing every day a multitude of periodic and real-time data coming from different providers and data sources. It is therefore able to semantically aggregate the data, in compliance with the Km4City multi-ontology and manage data: (i) having different access policies; and (ii) coming from traditional sources such as Open Data Portals, Web services, APIs and IoT/IoE networks. The aggregated data are the starting point for the services offered not only to the citizens but also to the public administrations and public-security service managers, enabling them to view a set of city dashboards ad hoc composed on their needs, for example, enabling them to modify and monitor public transportation strategies, offering the public services actually needed by citizens and tourists, monitor the air quality and traffic status to establish, if impose or not, traffic restrictions, etc. All the data and the new knowledge produced by the data analytics of the Snap4City platform can also be accessed, observing the permissions on each kind of data, thanks to the presence of an APIs complex system.

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“…In this regard, the authors in [35] enumerate the issues and requirements to develop semantic interoperability, while Gyrard et al [36] present a survey of ontology-based software tools for semantic interoperability. More specifically, semantic interoperability applied to IoT is studied in [37] and [38] through objects profiling and annotations. On top of it, some works have proposed methodologies to develop semantic interoperability for IoT, such as SEG3.0 [39].…”

Section: Related Workmentioning

confidence: 99%