A Linked Data Scalability Challenge: Concept Reuse Leads to Semantic Decay
This addresses a scalability issue for Semantic Web applications, where data quality declines as resources grow, which is incremental in highlighting a specific bottleneck.
The paper tackles the problem of semantic decay in Linked Data, demonstrating that increased concept reuse leads to reduced semantic richness, with empirical validation supporting this hypothesis.
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.