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Towards fully-fledged archiving for RDF datasets
Semantic Web ( IF 3.0 ) Pub Date : 2021-06-22 , DOI: 10.3233/sw-210434
Olivier Pelgrin 1 , Luis Galárraga 2 , Katja Hose 1
Affiliation  

Abstract

The dynamicity of RDF data has motivated the development of solutions for archiving, i.e., the task of storing and querying previous versions of an RDF dataset. Querying the history of a dataset finds applications in data maintenance and analytics. Notwithstanding the value of RDF archiving, the state of the art in this field is under-developed: (i) most existing systems are neither scalable nor easy to use, (ii) there is no standard way to query RDF archives, and (iii) solutions do not exploit the evolution patterns of real RDF data. On these grounds, this paper surveys the existing works in RDF archiving in order to characterize the gap between the state of the art and a fully-fledged solution. It also provides RDFev, a framework to study the dynamicity of RDF data. We use RDFev to study the evolution of YAGO, DBpedia, and Wikidata, three dynamic and prominent datasets on the Semantic Web. These insights set the ground for the sketch of a fully-fledged archiving solution for RDF data.



中文翻译:

走向成熟的 RDF 数据集归档

摘要

RDF 数据的动态性推动了归档解决方案的开发,即存储和查询 RDF 数据集以前版本的任务。查询数据集的历史可以找到数据维护和分析中的应用。尽管 RDF 归档具有价值,但该领域的最新技术尚未开发:(i) 大多数现有系统既不可扩展也不易于使用,(ii) 没有查询 RDF 归档的标准方法,以及 (iii) ) 解决方案没有利用真实 RDF 数据的演化模式。基于这些理由,本文调查了 RDF 归档中的现有工作,以描述最先进的技术与成熟的解决方案之间的差距。它还提供RDFev,一个研究 RDF 数据动态性的框架。我们使用 RDFev 来研究 YAGO、DBpedia 和 Wikidata 这三个语义 Web 上动态且突出的数据集的演变。这些见解为 RDF 数据的成熟归档解决方案的草图奠定了基础。

更新日期:2021-06-23
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