Most of the smart city solutions are transforming data to services for city users and operators, exploiting data and data analytics solutions. Smart City services usually integrate open and private data, static and real time data coming from the administrations and from private operators. The possibility of exploiting aggregated and re-conciliated data by reasoning algorithms enable the production of sophisticated services, such as those for implementing personal assistants, connected drive, smart services, etc. Different kinds of Smart City APIs depend on architectural solutions to pass from data to services. This paper presented a comparison among the data collection and aggregation solutions, by putting in evidence the needs of semantic interoperable aggregated data, in order to provide smart city services. According to the study, platform Sii-Mobility has been developed exploiting Km4City ontology and model for Smart City data aggregation and service production. The adopted Sii-Mobility solution for data ingestion and aggregation has been assessed in terms of cloud resources, identifying some of the drivers that may allow estimating the needed resources to cope with a range of different smart cities (taking into account, costs in the data ingestion, data analytics and front end/SPI). Then the paper, also presented a comparison of Smart City API at the state of the art vs those proposed by Sii-Mobility/Km4City APIs. The comparison has put in evidence the flexibility and coverage of the propose Smart City APIs. Finally, the data about the exploitation of the proposed API consumption have been presented. Km4City with Sii-Mobility tools and improvements is presently adopted by RESOLUTE H2020 and REPLICATE, H2020 European Commission research and development projects and by Ghost of MIUR project on Cagliari Metro Area. Please note that all the results presented are accessible as Affero GPL open sources on Github https://github.com/disit .
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