Semantic Information Integration with Linked Data Mashups Approaches. (28th April 2014)

• Record Type: Journal Article
• Authors: Hoang, Hanh Huu; Cung, Tai Nguyen-Phuoc; Truong, Duy Khanh; Hwang, Dosam; Jung, Jason J.
• Other Names: Kim Chong-Gun Academic Editor.
• Is Part Of: International journal of distributed sensor networks. (2014)
• Publication Date: 2014-04-28
• Subjects: Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1155/2014/813875
• Languages: English
• ISSNs: 1550-1329

Abstract

Abstract : The introduction of semantic web and Linked Data helps facilitate sharing of data on the Internet more easily. Subsequently, the resource description framework (RDF) is the standard in publishing structured data resources on the Internet and is used in interconnecting with other data resources. To remedy the data integration issues of the traditional web mashups, the semantic web technology uses the Linked Data based on RDF data model as the unified data model for combining, aggregating, and transforming data from heterogeneous data resources to build Linked Data mashups. There have been tremendous amounts of efforts of semantic web community to enable Linked Data mashups but there is still lack of a systematic survey on concepts, technologies, applications, and challenges. Therefore, in this paper, we investigate in detail semantic mashups research and application approaches in the information integration. This paper also presents a Linked Data mashup application as an illustration of the proposed approaches.