Abstract
Data models and semantics are a key aspect for the valorization of data in cross-domain applications and to obtain knowledge/insights beyond the original applications (vertical use cases). An important role of Big Data and a key fundament of its success is this capacity to discover and extract new knowledge beyond the original use of data, in order to learn, optimize processes and understand the hidden rules of our world. This works presents the different data models from standardization bodies such as IEEE PAR2530, ITU-T FG DPM, ETSI ISG CIM and oneM2M, W3C SSN, OMA LwM2M etc. An analysis and comparative among all of them and also the opportunities to link them in order to guarantee that we can obtain the major value through co-operation among cities and different departments. This work is contextualized in the principles from the Open and Agile Smart Cites (OASC) and linked initiatives focused on data management cross-cities and large scale pilots.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bischof, S., Karapantelakis, A., Nechifor, C., Sheth, A.P., Mileo, A., Barnaghi, P.: Semantic Modelling of Smart City Data. Kno.e.sis Publications. The Ohio Center of Excellence in Knowledge-Enabled Computing (Kno.e.sis) (2014). http://corescholar.libraries.wright.edu/knoesis/572
CityPulse: EU FP7 CityPulse Project, Grant No. 603095. http://www.ict-citypulse.eu
FIESTA-IoT: EU H2020 FIESTA-IoT project “Federated Interoperable Semantic IoT/cloud Testbeds and Applications”, Grant No. 643943 (2017)
Barnaghi, P., Wang, W., Dong, L., Wang, C.: A linked-data model for semantic sensor streams. In: 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on Green Computing and Communications (GreenCom), and IEEE Cyber, Physical and Social Computing, pp. 468–475 (2013)
Compton, M., Barnaghi, P., Bermudez, L., Garcıa-Castro, R., Corcho, O., Cox, S., Graybeal, J., Hauswirth, M., Henson, C., Herzog, A., Huang, V., Janowicz, K., Kelsey, W.D., Phuoc, D.L., Lefort, L., Leggieri, M., Neuhaus, H., Nikolov, A., Page, K., Passant, A., Sheth, A., Taylor, K.: The SSN ontology of the W3C semantic sensor network incubator group. Web Semant. Sci. Serv. Agents World Wide Web 17, 25–32 (2012)
ETSI ISG CIM: Context Information Management. https://portal.etsi.org/tb.aspx?tbid=854&SubTB=854
Jara, A.J., et al.: An analysis of context-aware data models for smart cities: towards fiware and etsi cim emerging data model. Int. Arch. Photogram. Remote Sens. Spat. Inf. Sci. 42 (2017)
HOP Ubiquitous: Homard overview and OMA LwM2M (2017). https://storage.googleapis.com/softfire/homard%20specifications.pdf
HOP Ubiquitous: Smart Spot Firmware (2017). https://storage.googleapis.com/softfire/smart-spot-specifications%20firmware-063d.pdf
Acknowledgments
This work is sponsored by HES-SO University. This work has been carried out in collaboration with the National University of Ireland Galway (NUIG) in the framework of the European Project FIESTA-IoT (Grant Agreement CNECT-ICT-643943) and the experiment FINETUNE; a the same time this work has included results carried out in collaboration with SmartSDK (Grant Agreement 723174) and SynchroniCity (Grant Agreement 732240). Finally, Andrea Gómez collaboration is supported as part of the scholarship (Industrial Doctorate) by UCAM.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Jara, A.J. et al. (2018). Smart Cities Semantics and Data Models. In: Rocha, Á., Guarda, T. (eds) Proceedings of the International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-319-73450-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-73450-7_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-73449-1
Online ISBN: 978-3-319-73450-7
eBook Packages: EngineeringEngineering (R0)