Algebraic Operations on Spatiotemporal Data Based on RDF

Author:

Zhu Lin,Li Nan,Bai Luyi

Abstract

In the context of the Semantic Web, the Resource Description Framework (RDF), a language proposed by W3C, has been used for conceptual description, data modeling, and data querying. The algebraic approach has been proven to be an effective way to process queries, and algebraic operations in RDF have been investigated extensively. However, the study of spatiotemporal RDF algebra has just started and still needs further attention. This paper aims to explore an algebraic operational framework to represent the content of spatiotemporal data and support RDF graphs. To accomplish our study, we defined a spatiotemporal data model based on RDF. On this basis, the spatiotemporal semantics and the spatiotemporal algebraic operations were investigated. We defined five types of graph algebras, and, in particular, the filter operation can filter the spatiotemporal graphs using a graph pattern. Besides this, we put forward a spatiotemporal RDF syntax specification to help users browse, query, and reason with spatiotemporal RDF graphs. The syntax specification illustrates the filter rules, which contribute to capturing the spatiotemporal RDF semantics and provide a number of advanced functions for building data queries.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hebei Province

Natural Science Foundation of Liaoning Province

Fundamental Research Funds for the Central Universities

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Geography, Planning and Development

Reference44 articles.

1. Resource description framework (RDF) model and syntax specification, W3C recommendationhttp://www.w3.org/TR/PR-rdf-syntax

2. Representing temporal knowledge in the semantic web: The extended 4d fluents approach;Batsakis,2011

3. Representing spatial relationships within smart cities using ontologies;Reed,2018

4. Spatio-Temporal Ontology Management Systems for Semantic;Kim;Web Inf.,2016

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Spatiotemporal Knowledge Graph Modeling and Persistence Supported by Database;2024 4th International Conference on Consumer Electronics and Computer Engineering (ICCECE);2024-01-12

2. Spatiotemporal Data Modeling Based on RDF;Advances in Systems Analysis, Software Engineering, and High Performance Computing;2023-12-15

3. Inconsistency Detection for Spatiotemporal Knowledge Graph with Entity Semantics and Spatiotemporal Features;J INF SCI ENG;2023

4. A general characterization of integrating and querying heterogeneous fuzzy spatiotemporal XML data;Earth Science Informatics;2023-09-05

5. τSQWRL: A TSQL2-Like Query Language for Temporal Ontologies Generated from JSON Big Data;Big Data Mining and Analytics;2023-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3