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Given the rapid growth of semantic web, a large amount of RDF data is being published to the Linked Open Data (LOD) cloud and other resources, hence the size and complexity of the RDF data has been continually and rapidly increasing. The context of ontology engineering, ontology understanding is the basis for its further development i.e. facilitating ontology applications, which is why there is an immediate need to develop more effective and efficient methods to simplify these complex datasets. The size and complexity of these datasets hinders their usage in broad domains. As the tool support for the process of ontology development by reuse is rather limited, users with limited Ontology Engineering experience get intimidated because of the intricacy associated with handling them. We propose a system, called RDF Briefer, which creates an RDF dataset’s synopsis, which provides an important insight and understanding of the dataset by discovering its underlying general structure, the current schema and identifying the key concepts in the dataset. As most of the datasets are publicly available at their respective Linked Data endpoints, RDF Briefer uses just the SPARQL endpoint’s URI as input and automatically discovers the current schema to generate an RDF dataset synopsis in the form of the most representative concepts and subgraphs, which we call RDF Briefs.