Blinked Data: Concepts, Characteristics, and Challenge

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.