Data Quality and Data Cleansing of Semantic Data

Amrapali Zaveri, Anisa Rula

Abstract:

Data cleaning; Data curation; Data quality; Data validation; Linked data; Quality assessment
Data quality is commonly conceived as a multidimensional construct defined as “fitness for use.” Data quality may depend on various factors (dimensions or characteristics) such as completeness, consistency, availability, etc. Data quality assessment involves the measurement of quality dimensions or criteria that are relevant to the use case. A metric or measure is a procedure for measuring a data quality dimension with the help of a tool. These metrics are heuristics that are designed to fit a specific assessment situation.
In this chapter, we first introduce the concepts of Linked Data quality and its dimensions and metrics. Then we provide definitions for 18 quality dimensions along with a total of 69 metrics to measure the dimensions.

Thereafter, we provide an overview of tools currently available for Linked Data quality assessment followed by an introduction to...