An Enhanced Framework to Ensure Big Data Veracity in Social Business Intelligence

Today, the Internet, characterized by its dynamics, is a fantastic source of data for companies. With the tools and techniques currently available, the processing of this data in real-time is no longer a concern; the main concern of decision-makers is the veracity of the data, especially in sensitive areas such as Business Intelligence. In this paper, we present a framework that tends to help decision-makers to ensure the veracity of Social Big Data to improve Social Business Intelligence. Our method checks the veracity of RDF triples based on domain ontology to control the structure of RDF triplets. Then to check the correspondences of the ontology properties, we use the WordNet semantic database, which allows us to check the subject and object classes of each triple RDF. Then the WikiData and DBpedia databases are used to ensure the veracity via a SPARQL quer