research-article

On-The-Fly Academic Linked Data Integration

Authors:

Mohamed Ragab Moaawad,

Hoda M. O. Mokhtar,

Haytham Tawfeek Al FeelAuthors Info & Claims

ICCDA '17: Proceedings of the International Conference on Compute and Data Analysis

Pages 114 - 122

https://doi.org/10.1145/3093241.3093276

Published: 19 May 2017 Publication History

Abstract

The web of Linked Open Data (LOD) has a prominent and rapid evolution recently. Over the last few years, LOD had developed to involve a wide range of various domains. Due to these facts, and the great interconnections among linked open datasets, linked data integration task had gained a huge attention and became a focal point of research. LOD applications aim to incorporate data from different LOD sources. Unfortunately, these sources of data are heterogeneous in schema and/or in vocabularies. Due to this heterogeneity, numerous challenges are emerging that have to be overcome. In this paper, a LOD integration framework is proposed, which aims to tackle these challenges. It works on integrating academic LOD datasets that reside in different LOD repositories with intrinsic schema and vocabularies heterogeneity. An automatic mapping technique in the integration processes is proposed in this paper. Consequently, an obvious decrease in execution time for the entire integration process, as well as, a great progress in the integrated data quality assessment metrics has been achieved.

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Ragab MSavateeve YWang WMoosaei RTiropanis TPoulovassilis AChapman AOliver HRoussos GChua TNgo CKumar RLauw HKa-Wei Lee R(2024)The 1st Workshop on Decentralised Search and RecommendationCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3641302(1705-1708)Online publication date: 13-May-2024
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Ragab MSavateev YOliver HTiropanis TPoulovassilis AChapman ARoussos G(2024)ESPRESSO: A Framework to Empower Search on the Decentralized WebData Science and Engineering10.1007/s41019-024-00263-wOnline publication date: 26-Nov-2024
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Index Terms

On-The-Fly Academic Linked Data Integration
1. Information systems
  1. Data management systems
    1. Information integration
      1. Mediators and data integration
  2. World Wide Web
    1. Web data description languages
      1. Semantic web description languages
        Resource Description Framework (RDF)

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cover image ACM Other conferences

ICCDA '17: Proceedings of the International Conference on Compute and Data Analysis

May 2017

307 pages

ISBN:9781450352413

DOI:10.1145/3093241

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of Florida: University of Florida

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 May 2017

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ICCDA '17

ICCDA '17: 2017 International Conference on Compute and Data Analysis

May 19 - 23, 2017

FL, Lakeland, USA

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Cited By

Ragab MAdidarma ATommasini R(2024)PAPAYA: A library for performance analysis of SQL-based RDF processing systemsSemantic Web10.3233/SW-243582(1-19)Online publication date: 5-Apr-2024
https://doi.org/10.3233/SW-243582
Ragab MSavateeve YWang WMoosaei RTiropanis TPoulovassilis AChapman AOliver HRoussos GChua TNgo CKumar RLauw HKa-Wei Lee R(2024)The 1st Workshop on Decentralised Search and RecommendationCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3641302(1705-1708)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3641302
Ragab MSavateev YOliver HTiropanis TPoulovassilis AChapman ARoussos G(2024)ESPRESSO: A Framework to Empower Search on the Decentralized WebData Science and Engineering10.1007/s41019-024-00263-wOnline publication date: 26-Nov-2024
https://doi.org/10.1007/s41019-024-00263-w
Ragab MSavateev YMoosaei RTiropanis TPoulovassilis AChapman ARoussos G(2023)ESPRESSO: A Framework for Empowering Search on Decentralized WebWeb Information Systems Engineering – WISE 202310.1007/978-981-99-7254-8_28(360-375)Online publication date: 21-Oct-2023
https://doi.org/10.1007/978-981-99-7254-8_28
Ragab M(2022)Towards Prescriptive Analyses of Querying Large Knowledge GraphsNew Trends in Database and Information Systems10.1007/978-3-031-15743-1_59(639-647)Online publication date: 29-Aug-2022
https://doi.org/10.1007/978-3-031-15743-1_59
Ragab MAwaysheh FTommasini R(2021)Bench-Ranking: A First Step Towards Prescriptive Performance Analyses For Big Data Frameworks2021 IEEE International Conference on Big Data (Big Data)10.1109/BigData52589.2021.9671277(241-251)Online publication date: 15-Dec-2021
https://doi.org/10.1109/BigData52589.2021.9671277
Sebbaq HEl Faddouli N(2021)MOOCs Semantic Interoperability: Towards Unified and Pedagogically Enriched Model for Building a Linked Data RepositoryDigital Technologies and Applications10.1007/978-3-030-73882-2_56(621-631)Online publication date: 26-Jun-2021
https://doi.org/10.1007/978-3-030-73882-2_56
Behan JRomero OZimányi E(2019)Multidimensional Integration of RDF DatasetsBig Data Analytics and Knowledge Discovery10.1007/978-3-030-27520-4_9(119-135)Online publication date: 3-Aug-2019
https://doi.org/10.1007/978-3-030-27520-4_9

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