Paper Info
Title
Blinked Data: Concepts, Characteristics, and Challenge
Abstract
Big Data refers to a large and complex data. It has four characteristics: volume, variety, velocity, and veracity. Typically, there are different types of Big Data: structured, semi-structured, and unstructured out of which the last two pose challenges in applications such as query processing. Especially, the query processing on semi-structured data is enormously challenging. Big Data and its characteristics have been documented in a large volume of literature however a comprehensive discussion of the characteristics of a specific type of Big Data is missing. Therefore, a solid understanding of these characteristics is sine quo non to process complex queries efficiently. Big Data is a generic term. We do not categorise Big Data in this paper instead we focus only on Big Linked Data which we called Blinked Data. It is a variant of Big semi-structured data which has a set of characteristics that are critical to modeling and processing. In this paper, we investigate the characteristics and challenges of Blinked Data. This paper aims to provide a comprehensive description of the concept 'Blinked Data'. In addition, this research presents the challenges in processing queries on Blinked Data through an empirical study.
Year
DOI
Venue
2014
10.1109/SERVICES.2014.80
Services
Keywords
Field
DocType
Big Data,query processing,Big Linked Data,Big semistructured data modeling,Big semistructured data processing,Blinked Data,query processing,Big Data,Blinked Data,Hadoop,Linked Data,MapReduce
Data science,Data mining,Data modeling,Computer science,Complex data type,Linked data,Big data,Database,RDF,Empirical research
Conference
ISSN
Citations 
PageRank 
2378-3818
2
0.40
References 
Authors
2
2
Name
Order
Citations
PageRank
Rafiqul Haque1119.56
Mohand-Said Hacid2969116.62