Archive | 2019

A Fuzzy Approach for Data Quality Assessment of Linked Datasets

 
 
 
 
 
 
 

Abstract


For several applications, an integrated view of linked data, denoted linked data mashup, is a critical requirement. Nonetheless, the quality of linked data mashups highly depends on the quality of the data sources. In this sense, it is essential to analyze data source quality and to make this information explicit to consumers of such data. This paper introduces a fuzzy ontology to represent the quality of linked data source. Furthermore, the paper shows the applicability of the fuzzy ontology in the process of evaluating data source quality used to build linked data mashups.

Volume None
Pages 399-406
DOI 10.5220/0007718803990406
Language English
Journal None

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