Home Communication Normalized City Analytics Based on a Semantic Interoperability Process
Normalized City Analytics Based on a Semantic Interoperability Process
26 March, 2024

The City Catalyst project aims to enhance better urban management, implementing the concept of sustainability and enabling semantic interoperability in cities in Smart Cities. Therefore, this paper presents a contextualization of Smart Cities and an overview of the remaining gaps that persist in terms of semantic interoperability. An introduction is also made at the level of ontologies. The NGSI-LD model is presented at the level of the generalized information referential and then, more specifically, the ontology layer. At last, scenarios were built, taking into account the context of the project, and, through these, tables were prepared with terms that constitute the glossary of terminologies. The work culminates with the mapping of the NGSI-LD using Neo4j which will serve as a basis for the Smart City systems to communicate with each other.

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This work was carried out within the project “CityCatalyst” reference POCI/LISBOA-01-0247-FEDER-046119, co-funded by Fundo Europeu de Desenvolvimento Regional (FEDER), through Portugal 2020 (P2020).

Authors:  Tiago Pereira, Nuno Soares, Mariana Pinto, Carlos Salgado, Ana Lima and Ricardo J. Machado


Soares, N., Monteiro, P., Duarte, F.J., Machado, R.J.: A unified reference model for smart cities. In: Santos, H., Pereira, G., Budde, M., Lopes, S., Nikolic, P. (eds.) Science and Technologies for Smart Cities. SmartCity 360 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 323, pp. 162–180. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-51005-3_16

Wu, C.-W., Lin, F.J., Wang, C.-H., Chang, N.: OneM2M-based IoT protocol integration. In: 2017 IEEE Conference on Standards for Communications and Networking, pp. 252–257. IEEE, Helsinki (2017). https://doi.org/10.1109/CSCN.2017.8088630

Rao, S., Chendanda, D., Deshpande, C., Lakkundi, V.: Implementing LWM2M in constrained IoT devices. In: 2015 IEEE Conference on Wireless Sensors, pp. 52–57. IEEE, Melaka (2015). https://doi.org/10.1109/ICWISE.2015.7380353

Jimenez, J., Koster, M., Tschofenig, H.: IPSO Smart Objects. https://omaspecworks.org/develop-with-oma-specworks/ipso-smart-objects/. Last accessed 13 Nov 2021

W3C: Semantic Sensor Network Ontology. https://www.w3.org/TR/vocab-ssn/. Last accessed 13 Dec 2021

Privat, G.: Guidelines for Modelling with NGSI-LD. ETSI White Paper, vol. 42 (2021)

Synchronicity. https://synchronicity-iot.eu/. Last accessed 11 Dec 2021

Si, A.N., Copromoção, E.M.: Sistema de Incentivos à Investigação e Desenvolvimento Tecnológico. Si I & Dt Co-Promoção, vol. 12 (2015)

Robinson, I., Webber, J., Eifrem, E.: Graph Databases: New Opportunities for Connected Data. O’Reilly, Farnham (2015)

Applications, S., Ontology, R.: TS 103 264—V3.1.1—SmartM2M; Smart Applications; Reference Ontology and oneM2M Mapping, vol. 1, pp. 1–25 (2020)

Bees, D., Frost, L., Bauer, M., Fisher, M., Li, W.: NGSI-LD API: for Context Information Management. ETSI, Antipolis (2019)

ETSI: GS CIM 009—V1.1.1—Context Information Management (CIM) NGSI-LD API, vol. 1, pp. 1–159 (2019)

Rocha, B.: LGeoSIM: um Modelo Semântico de Dados para Cidades Inteligentes. Universidade Federal do Rio Grande do Norte, Natal (2020)

Pereira, T.F., Matta, A., Mayea, C.M., Pereira, F., Monroy, N., Jorge, J., Rosa, T., Salgado, C.E., Lima, A., Machado, R.J., Magalhães, L., Adão, T., Guevara López, M.Á., Gonzalez, D.G.: A web-based voice interaction framework proposal for enhancing information systems user experience. Proc. Comput. Sci. 196, 235–244 (2021). https://doi.org/10.1016/j.procs.2021.12.010