Integrating social networks data in the process of promoting business and marketing applications is widely addressed by several researchers. However, regarding the isolation between social network platforms managing such data has become a challenging task facing data scientist. In this respect, the present paper is designed to put forward a special semantic data integration approach, whereby a unified presentation and access to social networks data can be maintained. To this end, the novel SNOWL (Social Network OWL) ontology aims to provide a new social network content modeling, following the UPON Lite ontology-construction methodology. The advanced ontology is not created from scratch; it is but a continuation of some previously devised ontologies, elaborated to integrate an additional selection of newly incorporated social entities, such as content and user popularity. Additionally, and for an effective advantage of the model to be gained, a special mapping of the social networks data has been firstly implemented to the designed ontology, developed on the basis of the RML mapping language. Secondly, the SNOWL ontology is evaluated through the OOPS! Pitfall tool. Finally, a set of SPARQL-based services has also been designed on top of the SNOWL ontology in a bid to ensure a unified access to the mapped social data.

若干研究人员广泛讨论了在促进业务和营销应用程序的过程中集成社交网络数据。但是，关于管理此类数据的社交网络平台之间的隔离已成为数据科学家面临的挑战性任务。在这方面，本文旨在提出一种特殊的语义数据集成方法，从而可以保持对社交网络数据的统一表示和访问。为此，新颖的SNOWL（社交网络OWL）本体旨在遵循UPON Lite本体构建方法，提供一种新的社交网络内容建模。高级本体不是从头开始创建的；它只是先前设计的一些本体的延续，这些本体是为整合新加入的社交实体的其他选择而精心设计的，例如内容和用户知名度。另外，为了获得该模型的有效优势，基于RML映射语言开发的社交网络数据的特殊映射已首先实现到设计的本体。其次，通过OOPS评估SNOWL本体！陷阱工具。最后，在SNOWL本体之上还设计了一套基于SPARQL的服务，以确保对映射的社交数据的统一访问。