Temporal RDF(S) Data Storage and Query with HBase | Zendy

Li Yan | Zendy; Zheqing Zhang | Zendy; Dan Yang | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Temporal RDF(S) Data Storage and Query with HBase

Author(s) -

Li Yan,

Zheqing Zhang,

Dan Yang

Publication year - 2020

Publication title -

journal of computing and information technology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.169

H-Index - 27

eISSN - 1846-3908

pISSN - 1330-1136

DOI - 10.20532/cit.2019.1004801

Subject(s) - rdf , computer science , metadata , storage model , rdf schema , sparql , database , metadata management , rdf query language , computer data storage , linked data , information retrieval , world wide web , semantic web , web search query , search engine , operating system , web query classification

Resource Description Framework (RDF) is a metadata model recommended by World Wide Web Consortium (W3C) for describing the Web resources. With the arrival of the era of big data, very large amounts of RDF data are continuously being created and need to be stored for management. The traditional centralized RDF storage models cannot meet the need of largescale RDF data storage. Meanwhile, the importance of temporal information management and processing has been acknowledged by academia and industry. In this paper, we propose a storage model to store temporal RDF data based on HBase. The proposed storage model applies the built-in time mechanism of HBase. Our experiments on LUBM dataset with temporal information added show that our storage model can store large temporal RDF data and obtain good query efficiency.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research