ITU‐T's Technical Reports and Specifications 707 The second layer is linked data layer. After gathering the raw data independently from the different sources, is to perform the converting from structured, unstructured and semi‐structured data to semantic data. This converting is made by means of an ontology (e.g., vocabularies, taxonomies) that describes these data. To perform this converting, our approach makes a priori converting based on standards. This process is made by converting from the OWL ontology to RDF triples. We observed existing approaches to perform converting only from structured data to RDF. The RDF datasets are stored in a CKAN repository, which is made public and can be accessed via the CKAN web interface and CKAN API37. From a technical perspective, the objective is to use common standards and techniques to extend the web by publishing data as RDF, creating well‐formatted RDF links between the data items, and performing search on the data via standardized languages such as SPARQL query language for RDF, performing search on the data via standardized languages such as SPARQL query language for RDF. Query interface, which enables the user community as well as the source institutions that offer these statistical data to pose queries upon it. This component consists of an online graphical interface as well as a SPARQL endpoint. The results of a query may be displayed as structured excel and RDF files to the users. Query interface layer is the sub‐layer providing the open data, consisting of two components: SparQL endpoint and Query processor. SparQL endpoint is the query interface of submission and retrieval results in open dataset submitted by Interconnect the dataset with other datasets. Query processor analyze the SparQL queries to verify which artifacts stored in the semantic database will be used. There are two components: Query analyzer and Semantic reasoner. Query analyzer analyzes SparQL query features to verification of the necessary elements to be used to return query results. Moreover, to improve the response time of a query uses the indices and metadata. Semantic reasoner is responsible for generating knowledge derived from inference about the immediate knowledge. One consideration is that this mechanism degrades the performance of a query. So this mechanism will be activated dynamically according to the complexity of the query submitted. Interconnect the dataset with other datasets is the sub‐layer that allows data fusion of semantic data38.The open data API is a RESTful, service‐oriented platform that allows developers to easily access datasets and create independent services through these calls. REST uses the HTTP protocol and, as such, requests use the common URL format. The API provides simple methods that developers can use to tap into the functionality and rich datasets, and gather information, in JSON or XML format, related to different indicators and topics39. A visualization service is delivered to the site and could include analytics, graphics, charting, and other ways of using the data. The enhanced visualization is built on top of published APIs in collaboration with third party open source applications. 5.3 Data visualization Data visualization is a modern branch of descriptive statistics meant to allow people to both understand and communicate data clearly and efficiently via the data graphics selected, such as tables, maps, charts and so on40. In the context of SSC for visualization, part of the data is stored in a digital file, typically in either text or binary form. Of course, potentially every piece of digital ephemera may be considered \"data\"—not just text, but bits and bytes representing images, audio, ____________________ 37 Franck M., Johan M. and Catherine F.; A survey of RDB to RDF translation approaches and tools. 38 Please see: http://lists.w3.org/Archives/Public/semantic‐web/2011Oct/0041.html. 39 Richardson L, Mike A, RESTful web APIs. 2013 40 Please see: http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf