loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Imen Sarray and Aziz Salah

Affiliation: Computer Science Department, Université du Québec à Montréal, 201 President Kennedy Avenue, Montreal and Canada

Keyword(s): Linked Data, RDF, SPARQL Queries, Semantic Web, Schema Construction, Resource Clustering, Query GUI Tool.

Related Ontology Subjects/Areas/Topics: Applications and Case-studies ; Artificial Intelligence ; Collaboration and e-Services ; e-Business ; Enterprise Information Systems ; Human-Machine Cooperation ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Semantic Web ; Soft Computing ; Symbolic Systems

Abstract: Much research has been undertaken to facilitate the construction of SPARQL queries, while other research has attempted to facilitate the construction of the RDF dataset schema to understand the structure of RDF datasets. However, there is no effective approach that brings together these two complementary objectives. This work is an effort in this direction. We propose an approach that allows assisted SPARQL query composition. Linked data interrogation is not only difficult because it requires mastering a query language such as SPARQL, but mainly because RDF datasets do not have an explicit schema as what you can expect in relational databases. This paper provides two complimentary solutions: synthesis of an interrogation-oriented schema and a form-based RDF Query construction tool, name EXPLO-RDF.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.191.87.157

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Sarray, I. and Salah, A. (2019). Assisted Composition of Linked Data Queries. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KEOD; ISBN 978-989-758-382-7; ISSN 2184-3228, SciTePress, pages 185-194. DOI: 10.5220/0008169601850194

@conference{keod19,
author={Imen Sarray. and Aziz Salah.},
title={Assisted Composition of Linked Data Queries},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KEOD},
year={2019},
pages={185-194},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008169601850194},
isbn={978-989-758-382-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KEOD
TI - Assisted Composition of Linked Data Queries
SN - 978-989-758-382-7
IS - 2184-3228
AU - Sarray, I.
AU - Salah, A.
PY - 2019
SP - 185
EP - 194
DO - 10.5220/0008169601850194
PB - SciTePress