Article

WebODE: a scalable workbench for ontological engineering

Authors:

Julio C. Arpírez,

Mariano Fernández-López,

Asunción Gómez-PérezAuthors Info & Claims

K-CAP '01: Proceedings of the 1st international conference on Knowledge capture

Pages 6 - 13

https://doi.org/10.1145/500737.500743

Published: 22 October 2001 Publication History

Abstract

This paper presents WebODE as a workbench for ontological engineering that not only allows the collaborative edition of ontologies at the knowledge level, but also provides a scalable architecture for the development of other ontology development tools and ontology-based applications. First, we will describe the knowledge model of WebODE, which has been mainly extracted and improved from the reference model of METHONTOLOGY's intermediate representations. Later, we will present its architecture, together with the main functionalities of the WebODE ontology editor, such as its import/export service, translation services, ontology browser, inference engine and axiom generator, and some services that have been integrated in the workbench: WebPicker, OntoMerge and the OntoCatalogue.

References

[1]

Benjamins, V.R., Fensel, D., Decker, S., G~mez-P~rez, A. (KA)2 : Building Ontologies for the Internet: a Mid Term Report. IJHCS, 51:687-712. 1999.]]

[2]

Berners-Lee, T., Fischetti, M. Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web by its Inventor. Harper. S Francisco. 1999.]]

Digital Library

[3]

Blazquez, M.; Fernandez-Lopez, M.; Garcia-Pinar, J.M.; Gomez-Perez, A. Building Ontologies at the Knowledge Level using the Ontology Design Environment. KAW98. Banff, Canada. 1998.]]

[4]

Chalupsky, H. OntoMorph: A Translation System for Symbolic Knowledge. KR-2000. 471-482. 2000.]]

[5]

Chaudhri V. K.; Farquhar A.; Fikes R.; Karp P. D.; Rice J. P. The Generic Frame Protocol 2.0. Technical Report, Stanford University.1997.]]

[6]

Corcho, O., Gomez-Perez, A. WebPicker: Knowledge Extraction from Web Resources. NLDB'01. Madrid. June, 2001.]]

Digital Library

[7]

DAML+OIL. http://www.daml.org]]

[8]

Domingue, J. Tadzebao and Webonto: Discussing, Browsing and Editing Ontologies on the Web. KAW98. Banff, Canada. 1998.]]

[9]

Domingue, J., Motta, E. A Knowledge-Based News Server Supporting Ontology-Driven Story Enrichment and Knowledge Retrieval. EKAW 1999.]]

Digital Library

[10]

Duineveld, A.; Studer, R.; Weiden, M; Kenepa, B.; Benjamis, R. WonderTools? A comparative study of ontological engineering tools. KAW99. Banff. 1999.]]

[11]

Farquhar A., Fikes R., Rice J., The Ontolingua Server: A Tool for Collaborative Ontology Construction. 10th Knowledge Acquisition for Knowledge-Based Systems Workshop, Banff, Canada. 1996.]]

[12]

Fensel, D., Angele, J., Decker, S., Erdmann, M., Schnurr, H., Staab, S., Studer, R., Witt, A. On2broker: Semantic-Based Access to Information Sources at the WWW. WebNet 99. Honolulu. USA. October, 1999.]]

[13]

Fern~ndez, M.; G~mez-P~rez, A.; Pazos, J.; Pazos, A. Building a Chemical Ontology using methontology and the Ontology Design Environment. IEEE Intelligent Systems and their applications. #4 (1):37-45. 1999.]]

Digital Library

[14]

Fridman, N., Musen, M. PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment. AAAI-2000. Austin, Texas. August, 2000.]]

[15]

Gomez-Perez, A. Evaluation of Ontologies. International Journal of Intelligent Systems. 16(3). March, 2001.]]

[16]

Horrocks, I., Fensel, D., Harmelen, F., Decker, S., Erdmann, M, Klein, M. OIL in a Nutshell. EKAW'00. Juan les Pins. France. October, 2000.]]

Digital Library

[17]

Kifer, M.; Lausen, G.; Wu, J. Logical Foundations of Object-Oriented and Frame-Based Languages. Journal of the ACM. 1995.]]

Digital Library

[18]

McGuinness, D., Fikes, R., Rice, J., Wilder, S. The Chimaera Ontology Environment. AAAI-2000. Austin, Texas. August, 2000.]]

Digital Library

[19]

MKBEEM. http://mkbeem.elibel.tm.fr]]

[20]

OILEd. http://img.cs.man.ac.uk/oil/]]

[21]

OntoEdit. http://www.ontoprise.de/co_produ_tool3.htm]]

[22]

OntoKnowledge. http://www.ontoknowledge.org]]

[23]

RDF. http://www.w3.org/TR/REC-rdf-syntax/]]

[24]

Swartout, B.; Ramesh P.; Knight, K.; Russ, T. Toward Distributed Use of Large-Scale Ontologies. AAAI Symposium on Ontological Engineering. Stanford. USA. March, 1997.]]

[25]

Using Protege-2000 to Edit RDF. Technical Report. Stanford University. http://www.smi.Stanford.edu/ projects/protege/protege-rdf/protege-rdf.html.]]

Cited By

Benabdellah AZekhnini KBag SGupta SOberoi S(2023)Smart Product Design Ontology Development for Managing Digital AgilityJournal of Global Information Management10.4018/JGIM.33359931:8(1-34)Online publication date: 9-Nov-2023
https://doi.org/10.4018/JGIM.333599
Hu FYang J(2020)A Fuzzy Performance Evaluation Model for Government Websites Based on Language Property and Balanced Score CardInternational Journal of Enterprise Information Systems10.4018/IJEIS.202004010916:2(148-163)Online publication date: 1-Apr-2020
https://dl.acm.org/doi/10.4018/IJEIS.2020040109
Wątróbski J(2020)Towards standardization in frameworks, tools and approaches dedicated to ontology building and managementProcedia Computer Science10.1016/j.procs.2020.09.063176(3345-3355)Online publication date: 2020
https://doi.org/10.1016/j.procs.2020.09.063
Show More Cited By

Index Terms

WebODE: a scalable workbench for ontological engineering
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
  2. Machine learning
    1. Learning settings
    2. Machine learning approaches
      1. Rule learning

Recommendations

WebODE: An Integrated Workbench for Ontology Representation, Reasoning, and Exchange
EKAW '02: Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web

We present WebODE as a scalable, integrated workbench for ontological engineering that eases the modelling of ontologies, the reasoning with ontologies and the exchange of ontologies with other ontology tools and ontology-based applications. We will ...
Building application ontologies from descriptions of Semantic Web Services

The existence of an increasing number of different ontologies used in semantic web service fields raises numerous interoperation and communication problems with respect to service discovery, composition, and execution. Current approaches for ontology ...
A model-driven approach of ontological components for on- line semantic web information retrieval

With the development of Web engineering and the advent of the Semantic Web, adding a semantic dimension to the Web by the deployment of ontologies has contributed to solve many problems. Ontologies specify the knowledge shared by a community of a target ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

K-CAP '01: Proceedings of the 1st international conference on Knowledge capture

October 2001

220 pages

ISBN:1581133804

DOI:10.1145/500737

Conference Chairs:
Yolanda Gil
University of Southern California/Information Sciences Institute
,
Mark Musen
Stanford University
,
Jude Shavlik
University of Wisconsin at Madison

Copyright © 2001 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]

Sponsors

SIGAI: ACM Special Interest Group on Artificial Intelligence

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 October 2001

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

K-CAP01

Sponsor:

SIGAI

K-CAP01: International Conference on Knowledge Capture

October 22 - 23, 2001

British Columbia, Victoria, Canada

Acceptance Rates

K-CAP '01 Paper Acceptance Rate 26 of 82 submissions, 32%;

Overall Acceptance Rate 55 of 198 submissions, 28%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

78
Total Citations
View Citations
999
Total Downloads

Downloads (Last 12 months)10
Downloads (Last 6 weeks)0

Reflects downloads up to 09 Aug 2024

Other Metrics

View Author Metrics

Citations

Cited By

Benabdellah AZekhnini KBag SGupta SOberoi S(2023)Smart Product Design Ontology Development for Managing Digital AgilityJournal of Global Information Management10.4018/JGIM.33359931:8(1-34)Online publication date: 9-Nov-2023
https://doi.org/10.4018/JGIM.333599
Hu FYang J(2020)A Fuzzy Performance Evaluation Model for Government Websites Based on Language Property and Balanced Score CardInternational Journal of Enterprise Information Systems10.4018/IJEIS.202004010916:2(148-163)Online publication date: 1-Apr-2020
https://dl.acm.org/doi/10.4018/IJEIS.2020040109
Wątróbski J(2020)Towards standardization in frameworks, tools and approaches dedicated to ontology building and managementProcedia Computer Science10.1016/j.procs.2020.09.063176(3345-3355)Online publication date: 2020
https://doi.org/10.1016/j.procs.2020.09.063
Othman AJemni M(2019)Designing High Accuracy Statistical Machine Translation for Sign Language Using Parallel CorpusJournal of Information Technology Research10.4018/JITR.201904010812:2(134-158)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.4018/JITR.2019040108
Zaibi DRiahi MMoussa F(2019)A Context-Aware Approach for Generating User Interfaces Based on Usability RequirementsJournal of Information Technology Research10.4018/JITR.201904010612:2(91-114)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.4018/JITR.2019040106
Batouta ZDehbi RTalea MOmar H(2019)Generative Matching Between Heterogeneous Meta-Model' Systems Based on Hybrid HeuristicJournal of Information Technology Research10.4018/JITR.201904010412:2(53-71)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.4018/JITR.2019040104
Jain AGupta B(2019)Feature Based Approach for Detection of Smishing Messages in the Mobile EnvironmentJournal of Information Technology Research10.4018/JITR.201904010212:2(17-35)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.4018/JITR.2019040102
Mohsen AIdrees AHassan H(2019)Emotion Analysis for Opinion Mining From TextInternational Journal of e-Collaboration10.4018/IJeC.201901010315:1(38-58)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.4018/IJeC.2019010103
Khalid SSmall NNeagu DSurr C(2019)A Study Proposing a Data Model for a Dementia Care Mapping DCM Data Warehouse for Potential Secondary Uses of Dementia Care DataInternational Journal of Healthcare Information Systems and Informatics10.4018/IJHISI.201901010514:1(61-79)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.4018/IJHISI.2019010105
Francis R(2019)Examining Healthcare Providers' Acceptance of Data From Patient Self-Monitoring Devices Using Structural Equation Modeling With the UTAUT2 ModelInternational Journal of Healthcare Information Systems and Informatics10.4018/IJHISI.201901010414:1(44-60)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.4018/IJHISI.2019010104
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents