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Semantic integration of heterogeneous classical data sources in ontological data warehouse

Published: 02 May 2018 Publication History

Abstract

The development of semantic web technologies and the expansion of the amount of data managed within companies databases lead to an enormous quantity of heterogeneous, distributed and autonomous data sources. However, this growth of information will give rise to real obstacles if we cannot maintain the pace with these changes and meet the needs of users. To succeed, it is necessary to find a solution for integrating data from traditional information systems into richer systems. In this perspective, Ontologies are a key component in solving the problem of semantic heterogeneity, thus enabling semantic interoperability between different web applications and services. In this paper, we provide and develop a semi-automatic approach for designing an ontological data warehouse from various sources. Our approach is to convert the different classical data sources (UML, XML, RDB) to local ontologies (OWL2), then merge these ontologies into a global ontological model based on syntactic, structural and semantic similarity measurement techniques to identify similar concepts and avoid their redundancy in the merge result. Our study is proven by a developed prototype that demonstrates the efficiency and power of our strategy and validates the theoretical concept.

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  • (2021)An Extended Semantic Interoperability Model for Distributed Electronic Health Record Based on Fuzzy Ontology SemanticsElectronics10.3390/electronics1014173310:14(1733)Online publication date: 19-Jul-2021
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cover image ACM Other conferences
LOPAL '18: Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications
May 2018
357 pages
ISBN:9781450353045
DOI:10.1145/3230905
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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Published: 02 May 2018

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Author Tags

  1. Integrating data
  2. OWL2
  3. RDB
  4. Semantic web
  5. UML
  6. XML
  7. data warehouse
  8. ontologies

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LOPAL '18
LOPAL '18: Theory and Applications
May 2 - 5, 2018
Rabat, Morocco

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LOPAL '18 Paper Acceptance Rate 61 of 141 submissions, 43%;
Overall Acceptance Rate 61 of 141 submissions, 43%

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Cited By

View all
  • (2022)Using Knowledge Graph Structures for Semantic Interoperability in Electronic Health Records Data ExchangesInformation10.3390/info1302005213:2(52)Online publication date: 21-Jan-2022
  • (2021)Multimatcher Model to Enhance Ontology Matching Using Background KnowledgeInformation10.3390/info1211048712:11(487)Online publication date: 22-Nov-2021
  • (2021)An Extended Semantic Interoperability Model for Distributed Electronic Health Record Based on Fuzzy Ontology SemanticsElectronics10.3390/electronics1014173310:14(1733)Online publication date: 19-Jul-2021
  • (2021)Review on Integrating Geospatial Big Datasets and Open Research IssuesIEEE Access10.1109/ACCESS.2021.30510849(10604-10620)Online publication date: 2021
  • (2020)Automating Data Integration in Adaptive and Data-Intensive Information SystemsInformation Systems10.1007/978-3-030-63396-7_2(20-34)Online publication date: 21-Nov-2020

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