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Article

Ontologies for semantically interoperable systems

Author:

Leo ObrstAuthors Info & Claims

CIKM '03: Proceedings of the twelfth international conference on Information and knowledge management

Pages 366 - 369

https://doi.org/10.1145/956863.956932

Published: 03 November 2003 Publication History

Abstract

In this paper, we discuss the use of ontologies for semantic interoperability and integration. We argue that information technology has evolved into a world of largely loosely coupled systems and as such, needs increasingly more explicit, machine-interpretable semantics. Ontologies in the form of logical domain theories and their knowledge bases offer the richest representations of machine-interpretable semantics for systems and databases in the loosely coupled world, thus ensuring greater semantic interoperability and integration. Finally, we discuss how ontologies support semantic interoperability in the real, commercial and governmental world.

References

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OWL Web Ontology Language Use Cases and Requirements. 2003, W3C Candidate Recommendation, August 18, 2003. http://ww1w.w3.org/TR/webont-req/.

[2]

Daconta, M., L. Obrst, K. Smith. 2003. The Semantic Web: The Future of XML, Web Services, and Knowledge Management. John Wiley, Inc., June, 2003.

Digital Library

[3]

Obrst, L., H. Liu. 2002. Knowledge Representation, Ontological Engineering, and Topic Maps. Chapter in XML Topic Maps: Creating and Using Topic Maps for the Web. Jack Park, ed. Addison-Wesley.

Digital Library

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D. L. McGuinness. 2002. Ontologies Come of Age. In Dieter Fensel, Jim Hendler, Henry Lieberman, and Wolfgang Wahlster, editors. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential. MIT Press, 2002.

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Obrst, L., G. Whittaker, A. Meng. 1999. Semantic Context for Object Exchange, AAAI Workshop on Context in AI Applications, Orlando, FL, July 19, 1999.

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Obrst, L., H. Liu, R. Wray. 2003. Ontologies for Corporate Web Applications. Artificial Intelligence Magazine, special issue on Ontologies, American Association for Artificial Intelligence, Chris Welty, ed., forthcoming, 2003

Digital Library

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Obrst, L., H. Liu, R. Wray, L. Wilson. 2002. Ontologies for Semantically Interoperable Electronic Commerce. In the Proceedings of ICEIMT'02, International Conference on Enterprise Modelling and Enterprise Integration Technologies (ICEIMT), and the Conference of the EI3-IC Initiative (Enterprise Inter- and Intra-Organisational Integration - International Consensus), Valencia, Spain, April 24-26, 2002, Kluwer Academic Publishers, 2002.

Digital Library

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Obrst, L., R. Wray, H. Liu. 2001. Ontological Engineering for B2B E-Commerce. In: Formal Ontology in Information Systems: Collected Papers from the Second International Conference, October 17-19, 2001, Ogunquit, ME. Chris Welty, Barry Smith, eds. ACM Publishing, http://www.fois.org/fois-2001/index.html.

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Smith, K., L. Obrst. 1999. Unpacking The Semantics of Source and Usage To Achieve Semantic Reconciliation In Large-Scale Information Systems, SIGMOD special issue on Semantic Interoperability, March, 1999, A. Sheth & A. Ouksel, eds.

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Department of Defense Metadata Registry. http://diides.ncr.disa.mil/xmlreg/user/index.cfm

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Cited By

Lin RAmith MWang CStrickley JTao C(2024)Dermoscopy Differential Diagnosis Explorer (D3X) Ontology to Aggregate and Link Dermoscopic Patterns to Differential Diagnoses: Development and Usability StudyJMIR Medical Informatics10.2196/4961312(e49613)Online publication date: 21-Jun-2024
https://doi.org/10.2196/49613
Farrokhnia MAalberg T(2024)What Information Are Researchers Looking for? Patterns of Users’ Information Needs in CIDOC CRMCataloging & Classification Quarterly10.1080/01639374.2024.233044962:3-4(302-324)Online publication date: 5-Apr-2024
https://doi.org/10.1080/01639374.2024.2330449
Karabulut EPileggi SGroth PDegeler V(2024)Ontologies in digital twins: A systematic literature reviewFuture Generation Computer Systems10.1016/j.future.2023.12.013153(442-456)Online publication date: May-2024
https://doi.org/10.1016/j.future.2023.12.013
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Index Terms

Ontologies for semantically interoperable systems
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Semantic networks
  2. Machine learning
    1. Machine learning approaches
      1. Rule learning
2. Theory of computation
  1. Logic

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Published In

cover image ACM Conferences

CIKM '03: Proceedings of the twelfth international conference on Information and knowledge management

November 2003

592 pages

ISBN:1581137230

DOI:10.1145/956863

General Chair:
Donald Kraft
Louisiana State University
,
Program Chairs:
Ophir Frieder
Illinois Institute of Technology
,
Joachim Hammer
University of Florida
,
Sajda Qureshi
University of Nebraska, Omaha
,
Len Seligman
The MITRE Corporation

Copyright © 2003 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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Published: 03 November 2003

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November 3 - 8, 2003

LA, New Orleans, USA

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Lin RAmith MWang CStrickley JTao C(2024)Dermoscopy Differential Diagnosis Explorer (D3X) Ontology to Aggregate and Link Dermoscopic Patterns to Differential Diagnoses: Development and Usability StudyJMIR Medical Informatics10.2196/4961312(e49613)Online publication date: 21-Jun-2024
https://doi.org/10.2196/49613
Farrokhnia MAalberg T(2024)What Information Are Researchers Looking for? Patterns of Users’ Information Needs in CIDOC CRMCataloging & Classification Quarterly10.1080/01639374.2024.233044962:3-4(302-324)Online publication date: 5-Apr-2024
https://doi.org/10.1080/01639374.2024.2330449
Karabulut EPileggi SGroth PDegeler V(2024)Ontologies in digital twins: A systematic literature reviewFuture Generation Computer Systems10.1016/j.future.2023.12.013153(442-456)Online publication date: May-2024
https://doi.org/10.1016/j.future.2023.12.013
Pinon S(2023)Business User-Oriented Recommender System of DataResearch Challenges in Information Science: Information Science and the Connected World10.1007/978-3-031-33080-3_44(613-621)Online publication date: 23-May-2023
https://doi.org/10.1007/978-3-031-33080-3_44
Potember RBalhana CObrst L(2022)An Introduction to Semantic Threat Analysis for Systems Security EngineeringINCOSE International Symposium10.1002/iis2.1294532:1(498-513)Online publication date: 26-Sep-2022
https://doi.org/10.1002/iis2.12945
GRITSENKO VGLADUN AKHALA KMARTÍNEZ-BÉJAR R(2021)Semantical Similarity Evaluation Method of Concepts for Comparison of Ontologies in Applied Problems of Artificial IntelligenceKibernetika i vyčislitelʹnaâ tehnika10.15407/kvt205.03.0052021:3(205)(5-25)Online publication date: 11-Sep-2021
https://doi.org/10.15407/kvt205.03.005
Sharma AColonna G(2021)System-Wide Pollution of Biomedical Data: Consequence of the Search for Hub Genes of Hepatocellular Carcinoma Without Spatiotemporal ConsiderationMolecular Diagnosis & Therapy10.1007/s40291-020-00505-3Online publication date: 21-Jan-2021
https://doi.org/10.1007/s40291-020-00505-3
Bakirtzis GSherburne TAdams SHorowitz BBeling PFleming C(2021)An ontological metamodel for cyber-physical system safety, security, and resilience coengineeringSoftware and Systems Modeling10.1007/s10270-021-00892-zOnline publication date: 1-Jun-2021
https://doi.org/10.1007/s10270-021-00892-z
Li SAbel MNegre E(2021)A collaboration context ontology to enhance human-related collaboration into Industry 4.0Cognition, Technology & Work10.1007/s10111-021-00677-wOnline publication date: 27-Mar-2021
https://doi.org/10.1007/s10111-021-00677-w
Cao QSamet AZanni-Merk Cde Bertrand de Beuvron FReich CThakker DPatel PAli MShah T(2020)Combining chronicle mining and semantics for predictive maintenance in manufacturing processesSemantic Web10.3233/SW-20040611:6(927-948)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.3233/SW-200406
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