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.
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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.
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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
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DOI: https://doi.org/10.1007/978-3-319-73450-7_8
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