Purpose
– One of the most important categories in linked open data (LOD) quality models is “data accessibility.” The purpose of this paper is to propose some metrics and indicators for assessing data accessibility in LOD and the semantic web context.
Design/methodology/approach
– In this paper, at first the authors consider some data quality and LOD quality models to review proposed subcategories for data accessibility dimension in related texts. Then, based on goal question metric (GQM) approach, the authors specify the project goals, main issues and some questions. Finally, the authors propose some metrics for assessing the data accessibility in the context of the semantic web.
Findings
– Based on GQM approach, the authors determined three main issues for data accessibility, including data availability, data performance, and data security policy. Then the authors created four main questions related to these issues. As a conclusion, the authors proposed 27 metrics for measuring these questions.
Originality/value
– Nowadays, one of the main challenges regarding data quality is the lack of agreement on widespread quality metrics and practical instruments for evaluating quality. Accessibility is an important aspect of data quality. However, few researches have been done to provide metrics and indicators for assessing data accessibility in the context of the semantic web. So, in this research, the authors consider the data accessibility dimension and propose a comparatively comprehensive set of metrics.
Improving data quality in the linked open data: a survey
