Co-evolution of RDF Datasets

TL;DR

This paper addresses the challenge of managing RDF dataset co-evolution, proposing a property-oriented conflict resolution approach that improves data quality during replication and synchronization in Linked Data environments.

Contribution

It introduces a novel property-oriented co-evolution management approach that leverages RDF semantics for conflict resolution, enhancing data consistency and quality.

Findings

Improves data quality in RDF dataset replicas.

Enhances synchronization during RDF data co-evolution.

Demonstrates effectiveness on DBpedia-live dataset.

Abstract

Linking Data initiatives have fostered the publication of large number of RDF datasets in the Linked Open Data (LOD) cloud, as well as the development of query processing infrastructures to access these data in a federated fashion. However, different experimental studies have shown that availability of LOD datasets cannot be always ensured, being RDF data replication required for envisioning reliable federated query frameworks. Albeit enhancing data availability, RDF data replication requires synchronization and conflict resolution when replicas and source datasets are allowed to change data over time, i.e., co-evolution management needs to be provided to ensure consistency. In this paper, we tackle the problem of RDF data co-evolution and devise an approach for conflict resolution during co-evolution of RDF datasets. Our proposed approach is property-oriented and allows for exploiting semantics about RDF properties during co-evolution management. The quality of our approach is empirically evaluated in different scenarios on the DBpedia-live dataset. Experimental results suggest that proposed proposed techniques have a positive impact on the quality of data in source datasets and replicas.