A Survey on Semantic Sensor Web: Sensor Ontology, Mapping and Query <s> The Mapping Languages <s> RDB2RDF mapping has been a hot topic in the Semantic Web research community. In order to standardize the mapping mechanism and then facilitate sharing and reuse of the mapping definitions, the W3C RDB2RDF Working Group published a general purpose RDB2RDF mapping language standard, R2RML, in September 2012. Several mapping tools or ongoing projects have been gradually supporting the R2RML standard. But they rarely write up and report the design and implementation techniques for the mapping algorithms. This paper presents the algorithm design of a prototype R2RML processor for materializing RDF view of relational data. Experimental tests on the effectiveness and the run-time efficiency of the algorithm were conducted with the W3C-defined R2RML mapping test cases. The experimental results show that the proposed RDB2RDF mapping approach is implementable with Java language, and the run-time of the algorithm exhibits a linear growth rate as the generated RDF triples size increases. <s> BIB001 </s> A Survey on Semantic Sensor Web: Sensor Ontology, Mapping and Query <s> The Mapping Languages <s> Despite the signicant number of existing tools, incorporating data from multiple sources and dierent formats into the Linked Open Data cloud remains complicated. No mapping formalisation exists to dene how to map such heterogeneous sources into rdf in an integrated and interoperable fashion. This paper introduces the rml mapping language, a generic language based on an extension over r2rml, the w3c standard for mapping relational databases into rdf. Broadening r2rml’s scope, the language becomes source-agnostic and extensible, while facilitating the denition of mappings of multiple heterogeneous sources. This leads to higher integrity within datasets and richer interlinking among resources. <s> BIB002
D2RQ is a declarative language for mapping relational database schemas to RDF vocabularies and OWL ontologies. It is realized as the Jena Figure. It can pack one or more relational database to a virtual, read-only RDF graphs. Its mapping processor is D2R server which can use a customizable D2RQ mapping to map database content into the RDF format and allow the RDF data to be browsed and searched. R 2 O is the declarative mapping description language based on the XML. It can describe mapping relations between the relations and the properties of the relation database and the basic elements of RDFS/OWL ontology. It can be realized by ODEMapster mapping processor. R2RML is the mapping language announced by the W3C RDB2RDF in September 2012. It can express the mapping from RDB to RDF by using a form of one or more triples mapping elements. R2RML mappings are themselves RDF graphs and written down in Turtle syntax. R2RML processor will offer a virtual SPARQL endpoint over the mapped relational data, or generate RDF files, or offer a Linked Data interface. In reference BIB001 , R2RML processor prototype is designed. It can transform RDB to RDF automatically. Morph-RDB is an RDB2RDF engine which follows the R2RML specification. It can generate RDF data from a relational database according to the R2RML mapping descriptions. The RDF Mapping language (RML) is a generic mapping language defined to express customized mapping rules from heterogeneous data structures and serializations to the RDF data model. RML is defined as a superset of the W3C-standardized mapping language, R2RML, that maps data in relational databases to the RDF data model. RML extends R2RML's applicability and broaden R2RML's scope to define mappings of data in other formats too BIB002 . With RML, you can define the rules to map any heterogeneous data such as DB, CSV, XML and JSON etc to the RDF data model. A prototype RML processor is implemented in Java based on the mapping-driven model. Ontop is a platform to query databases as Virtual RDF Graphs using SPARQL. It's extremely fast and is packed with features. It concludes two components: Quest and ontopPro. Quest is the SPARQL engine that comes with ontop, and ontopPro is a powerful mapping editor to allow you to define data sources for your ontologies and to map them using a powerful and intuitive mapping language. The data sources conclude a variety of data formats such as DB, CSV, XML, XSL etc. S 2 O is the extension of R 2 O mapping language, and it mainly shows the mapping relationship from the sensor stream data to the ontology. S 2 O mapping documents describe how to convert the stream data source to the ontology. It is the extensional version of R 2 O. In order to support stream data, S 2 O can describe the stream data model. On the basis of R 2 O, new correspondence relationships are added: streamschema-desc. The streamType property is increased to describe a kind of data acquisition stream. The timestamp-desc element is increased to declare the stream timestamp property. The other classes and properties defined by R 2 O are all suitable for stream pattern.