A Linked Data Scalability Challenge: Concept Reuse Leads to Semantic Decay

TL;DR

This paper introduces a measure of semantic richness in Linked Data, demonstrating that increased reuse of concepts leads to semantic decay, which poses a scalability challenge for the Semantic Web.

Contribution

It proposes a new measure of semantic richness and empirically validates that concept reuse reduces semantic quality, highlighting a key scalability issue.

Findings

Semantic richness decreases with concept reuse

Empirical validation supports the semantic decay hypothesis

Addresses a core scalability challenge in Linked Data

Abstract

The increasing amount of available Linked Data resources is laying the foundations for more advanced Semantic Web applications. One of their main limitations, however, remains the general low level of data quality. In this paper we focus on a measure of quality which is negatively affected by the increase of the available resources. We propose a measure of semantic richness of Linked Data concepts and we demonstrate our hypothesis that the more a concept is reused, the less semantically rich it becomes. This is a significant scalability issue, as one of the core aspects of Linked Data is the propagation of semantic information on the Web by reusing common terms. We prove our hypothesis with respect to our measure of semantic richness and we validate our model empirically. Finally, we suggest possible future directions to address this scalability problem.