当前位置: X-MOL 学术Comput. Sci. Rev. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Storage, partitioning, indexing and retrieval in Big RDF frameworks: A survey
Computer Science Review ( IF 12.9 ) Pub Date : 2020-10-15 , DOI: 10.1016/j.cosrev.2020.100309
Tanvi Chawla , Girdhari Singh , Emmanuel S. Pilli , M.C. Govil

Resource Description Framework (RDF) is increasingly being used to model data on the web. RDF model was designed to support easy representation and exchange of information on the web. RDF is queried using SPARQL, a standard query language recommended by W3C. The growth in acceptance of RDF format can be attributed to its flexible and reusable nature. The size of RDF data is steadily increasing as many government organizations and companies are using RDF for data representation and exchange. This resulted in the need for developing distributed RDF frameworks that can efficiently manage RDF data on large scale i.e. Big RDF data. These scalable distributed RDF data management systems competent enough to handle Big RDF data can also be termed as Big RDF frameworks. The proliferation of RDF data has made RDF data management a difficult task. In this survey, we provide an extensive literature on Big RDF frameworks from the aspect of storage, partitioning, indexing, query optimization and processing. A taxonomy of the tools and technologies used for storage and retrieval of Big RDF data in these systems has been presented. The comparative evaluation of some Big RDF frameworks based on query performance and our observations from this evaluation are described. The research challenges identified during the study of these systems are elaborated to suggest promising directions for future research.



中文翻译:

Big RDF框架中的存储,分区,索引和检索:一项调查

资源描述框架(RDF)越来越多地用于对Web上的数据进行建模。RDF模型旨在支持在Web上轻松表示和交换信息。使用SPARQL(W3C推荐的标准查询语言)查询RDF。RDF格式接受度的增长可以归因于其灵活和可重用的性质。由于许多政府组织和公司正在使用RDF进行数据表示和交换,因此RDF数据的大小正在稳定增长。这导致需要开发分布式RDF框架,该框架可以有效地大规模管理RDF数据,即Big RDF数据。这些足以处理Big RDF数据的可伸缩分布式RDF数据管理系统也可以称为Big RDF框架。RDF数据的激增使RDF数据管理成为一项艰巨的任务。在此调查中,我们从存储,分区,索引,查询优化和处理方面提供了有关Big RDF框架的大量文献。已经介绍了在这些系统中用于存储和检索大RDF数据的工具和技术的分类。描述了基于查询性能的一些Big RDF框架的比较评估,以及我们根据评估得出的观察结果。这些系统的研究过程中确定的研究挑战已详细阐述,为未来的研究提供了有希望的方向。描述了基于查询性能的一些Big RDF框架的比较评估,以及我们根据评估得出的观察结果。这些系统的研究过程中确定的研究挑战已详细阐述,为未来的研究提供了有希望的方向。描述了基于查询性能的一些Big RDF框架的比较评估,以及我们根据评估得出的观察结果。这些系统的研究过程中确定的研究挑战已详细阐述,为未来的研究提供了有希望的方向。

更新日期:2020-10-16
down
wechat
bug