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Co-evolution of RDF Datasets

机译:RDF数据集的共同演变

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摘要

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.
机译:链接数据倡议促进了大量的链接的开放数据(LOD)云RDF数据集的出版物,以及对查询处理的基础设施的发展在联合的方式来访问这些数据。然而,不同的实验研究表明,LOD数据集的可用性不能始终保证,是对设想可靠联合查询框架所需的RDF数据复制。尽管增强数据的可用性,RDF数据复制需要同步和解决冲突时副本和源数据集被允许变化数据随着时间的推移,即共同进化管理需要被提供以确保一致性。在本文中,我们将处理RDF数据协同进化的问题,并制定RDF数据集的协同进化过程中解决冲突的方法。我们提出的方法是财产为导向,以允许协同进化过程中的管理利用约RDF属性的语义。我们的质量方针在对DBpedia中,现场数据集不同的场景是根据经验评估。实验结果表明,提出建议的技术对数据源的数据集和副本的质量产生积极的影响。

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