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Community-driven Consolidated Linked Data

Community-driven Consolidated Linked Data

Aman Shakya, Hideaki Takeda, Vilas Wuwongse
Copyright: © 2011 |Pages: 31
ISBN13: 9781609605933|ISBN10: 1609605934|EISBN13: 9781609605940
DOI: 10.4018/978-1-60960-593-3.ch009
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MLA

Shakya, Aman, et al. "Community-driven Consolidated Linked Data." Semantic Services, Interoperability and Web Applications: Emerging Concepts, edited by Amit Sheth, IGI Global, 2011, pp. 228-258. https://doi.org/10.4018/978-1-60960-593-3.ch009

APA

Shakya, A., Takeda, H., & Wuwongse, V. (2011). Community-driven Consolidated Linked Data. In A. Sheth (Ed.), Semantic Services, Interoperability and Web Applications: Emerging Concepts (pp. 228-258). IGI Global. https://doi.org/10.4018/978-1-60960-593-3.ch009

Chicago

Shakya, Aman, Hideaki Takeda, and Vilas Wuwongse. "Community-driven Consolidated Linked Data." In Semantic Services, Interoperability and Web Applications: Emerging Concepts, edited by Amit Sheth, 228-258. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-60960-593-3.ch009

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Abstract

User-generated content can help the growth of linked data. However, there are a lack of interfaces enabling ordinary people to author linked data. Secondly, people have multiple perspectives on the same concept and different contexts. Thirdly, there are not enough ontologies to model various data. Therefore, the authors of this chapter propose an approach to enable people to share various data through an easy-to-use social platform. Users define their own concepts and multiple conceptualizations are allowed. These are consolidated using semi-automatic schema alignment techniques supported by the community. Further, concepts are grouped semi-automatically by similarity. As a result of consolidation and grouping, informal lightweight ontologies emerge gradually. The authors have implemented a social software system, called StYLiD, to realize the approach. It can serve as a platform motivating people to bookmark and share different things. It may also drive vertical portals for specific communities with integrated data from multiple sources. Some experimental observations support the validity of the approach.

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