![]() Each of these taxonomies clearly places entities in a classification which is beneficial for multiple stakeholders and for multiple domains in urban smartness targeting. In particular, a taxonomy is proposed for each of the main SC data entities, namely, the “D Taxonomy” for the data production, the “M Taxonomy” for data analytics methods, and the “S Taxonomy” for smart services. The review results generate useful taxonomies for data scientists in the SC context, which offers clear guidelines for corresponding future works. A survey protocol is followed to reach both quantitative and semantically important entities. The survey focuses on data harvesting and data mining processes over repeated SC data cycles. The aim of this article is to “connect the pieces” among Data Science and SC domains, with a systematic literature review which identifies the core topics, services, and methods applied in SC data monitoring. These ecosystems consider SCs as data production and sharing engines, setting new challenges for building effective SC architectures and novel services. Smart cities (SCs) are becoming highly sophisticated ecosystems at which innovative solutions and smart services are being deployed. ![]()
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