Sharing data on the grid using ontologies and distributed SPARQL queries

被引:2
|
作者
Langegger, Andreas [1 ]
Bloechl, Martin [1 ]
Woess, Wolfram [1 ]
机构
[1] Johannes Kepler Univ Linz, Inst Appl Knowledge Proc, Altenberger Str 69, A-4040 Linz, Austria
关键词
D O I
10.1109/DEXA.2007.129
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The vision of the Semantic Web is to make Web content machine-readable. To describe data, the Resource Description Framework has been extended with a schema-level and description logics (e.g. RDF-S and OWL DL). To successfully retrieve data described by RDF-based ontologies, the query language SPARQL is currently being developed at W3C. However, although SPARQL also provides a client/server protocol, currently queries are targeted to single sites only. For a large-scale data integration, which is the scope of a middleware developed within the Austrian Grid project, it is necessary to execute queries on distributed data nodes. Because of the large amount of research undertaken in the field of relational database systems, it is reasonable to apply relational algebra to SPARQL query processors. In fact, most RDF triple stores are based on relational database systems. In this paper, several concepts are proposed to enable the integration of heterogeneous, distributed data sources with SPARQL.
引用
收藏
页码:450 / +
页数:2
相关论文
共 50 条
  • [1] Towards Efficient Distributed SPARQL Queries on Linked Data
    Li, Xuejin
    Niu, Zhendong
    Zhang, Chunxia
    ALGORITHMS AND ARCHITECTURES FOR PARALLEL PROCESSING, ICA3PP 2014, PT II, 2014, 8631 : 259 - 272
  • [2] WODII: a solution to process SPARQL queries over distributed data sources
    Ahmed Rabhi
    Rachida Fissoune
    Cluster Computing, 2020, 23 : 2315 - 2322
  • [3] WODII: a solution to process SPARQL queries over distributed data sources
    Rabhi, Ahmed
    Fissoune, Rachida
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2020, 23 (03): : 2315 - 2322
  • [4] Lower and Upper Bounds for SPARQL Queries over OWL Ontologies
    Glimm, Birte
    Kazakov, Yevgeny
    Kollia, Ilianna
    Stamou, Giorgos
    PROCEEDINGS OF THE TWENTY-NINTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2015, : 109 - 115
  • [6] Efficient distributed SPARQL queries on Apache Spark
    Albahli S.
    International Journal of Advanced Computer Science and Applications, 2019, 10 (08): : 564 - 568
  • [7] Clustering Remote RDF Data Using SPARQL Update Queries
    Qi, Letao
    Lin, Harris T.
    Honavar, Vasant
    2013 IEEE 29TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING WORKSHOPS (ICDEW), 2013, : 236 - 242
  • [8] SPARQL Queries over Ontologies Under the Fixed-Domain Semantics
    Rudolph, Sebastian
    Schweizer, Lukas
    Yao, Zhihao
    PRICAI 2019: TRENDS IN ARTIFICIAL INTELLIGENCE, PT I, 2019, 11670 : 486 - 499
  • [9] Scraping Data from Web Pages Using SPARQL Queries
    Burget, Radek
    WEB ENGINEERING, ICWE 2023, 2023, 13893 : 293 - 300
  • [10] Using Machine Learning and Routing Protocols for Optimizing Distributed SPARQL Queries in Collaboration
    Warnke, Benjamin
    Fischer, Stefan
    Groppe, Sven
    COMPUTERS, 2023, 12 (10)