Storage Solution of Spatial-Temporal Data for Water Monitoring Infrastructures Used in Smart Cities
This article presents a novel definition of a declarative mapping language, which is able to map precisely and unambiguously the semantics of a domain conceptualization (defined as an ontology) into queries to a set of data sources, where the data is residing. In this way, a system making use of this mapping language is able to access the data actually stored in the data sources thought a semantically rich representation. The mapping model proposed in this paper is also an ontology and therefore is machine understandable: it can be shared with other users or systems, processed by external tools for consistency checking, or collaboratively created and so on. Besides the contributions of the mapping model itself, this paper introduces the concepts of Semantic Join and Semantic Identifiers: a declarative approach to semantic data fusion and entity resolution over multiple unrelated databases, which allow to define extremely expressive mapping.