Data modeling and harmonization with OWL: Opportunities and lessons learned

John L. McCarthy; Denise Warzel; Elisa Kendall; Bruce Bargmeyer; Harold Solbrig; Kevin Keck; Fred Gey

Data modeling and harmonization with OWL: Opportunities and lessons learned

John L. McCarthy, Denise Warzel, Elisa Kendall, Bruce Bargmeyer, Harold Solbrig, Kevin Keck, Fred Gey

Research output: Contribution to journal › Conference article › peer-review

Abstract

Experience from recent projects helps illuminate the promises and limitations of OWL to specify, review, refine, harmonize and integrate diverse data and concept models. One of the attractive features of OWL is that it can be used by inference engines to help augment queries through inferred semantic relationships. But OWL, like SQL, is only a computer programming language. Using it to review and refine representations of data, metadata, and concept systems, including terminologies, thesauri, and ontologies, requires a well-defined abstraction layer - which itself can be specified in terms of OWL. In order to optimize, harmonize and integrate such information effectively for large scale projects, OWL definitions and relationships should be specified in terms of a standard metamodel, such as ISO/IEC 11179-3, Edition 3.

Original language	English (US)
Pages (from-to)	86-97
Number of pages	12
Journal	CEUR Workshop Proceedings
Volume	524
State	Published - Dec 1 2009
Externally published	Yes
Event	5th International Workshop on Semantic Web Enabled Software Engineering, SWESE 2009 - Collocated with the 8th International Semantic Web Conference, ISWC 2009 - Washington, DC, United States Duration: Oct 25 2009 → Oct 25 2009

Keywords

Data modeling
ISO 11179
Metadata
Metadata registration
OWL
UML

ASJC Scopus subject areas

General Computer Science

Cite this

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title = "Data modeling and harmonization with OWL: Opportunities and lessons learned",

abstract = "Experience from recent projects helps illuminate the promises and limitations of OWL to specify, review, refine, harmonize and integrate diverse data and concept models. One of the attractive features of OWL is that it can be used by inference engines to help augment queries through inferred semantic relationships. But OWL, like SQL, is only a computer programming language. Using it to review and refine representations of data, metadata, and concept systems, including terminologies, thesauri, and ontologies, requires a well-defined abstraction layer - which itself can be specified in terms of OWL. In order to optimize, harmonize and integrate such information effectively for large scale projects, OWL definitions and relationships should be specified in terms of a standard metamodel, such as ISO/IEC 11179-3, Edition 3.",

keywords = "Data modeling, ISO 11179, Metadata, Metadata registration, OWL, UML",

author = "McCarthy, {John L.} and Denise Warzel and Elisa Kendall and Bruce Bargmeyer and Harold Solbrig and Kevin Keck and Fred Gey",

year = "2009",

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T2 - 5th International Workshop on Semantic Web Enabled Software Engineering, SWESE 2009 - Collocated with the 8th International Semantic Web Conference, ISWC 2009

AU - McCarthy, John L.

AU - Warzel, Denise

AU - Kendall, Elisa

AU - Bargmeyer, Bruce

AU - Solbrig, Harold

AU - Keck, Kevin

AU - Gey, Fred

PY - 2009/12/1

Y1 - 2009/12/1

N2 - Experience from recent projects helps illuminate the promises and limitations of OWL to specify, review, refine, harmonize and integrate diverse data and concept models. One of the attractive features of OWL is that it can be used by inference engines to help augment queries through inferred semantic relationships. But OWL, like SQL, is only a computer programming language. Using it to review and refine representations of data, metadata, and concept systems, including terminologies, thesauri, and ontologies, requires a well-defined abstraction layer - which itself can be specified in terms of OWL. In order to optimize, harmonize and integrate such information effectively for large scale projects, OWL definitions and relationships should be specified in terms of a standard metamodel, such as ISO/IEC 11179-3, Edition 3.

AB - Experience from recent projects helps illuminate the promises and limitations of OWL to specify, review, refine, harmonize and integrate diverse data and concept models. One of the attractive features of OWL is that it can be used by inference engines to help augment queries through inferred semantic relationships. But OWL, like SQL, is only a computer programming language. Using it to review and refine representations of data, metadata, and concept systems, including terminologies, thesauri, and ontologies, requires a well-defined abstraction layer - which itself can be specified in terms of OWL. In order to optimize, harmonize and integrate such information effectively for large scale projects, OWL definitions and relationships should be specified in terms of a standard metamodel, such as ISO/IEC 11179-3, Edition 3.

KW - Data modeling

KW - ISO 11179

KW - Metadata

KW - Metadata registration

KW - OWL

KW - UML

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M3 - Conference article

AN - SCOPUS:84891462595

SN - 1613-0073

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JO - CEUR Workshop Proceedings

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Y2 - 25 October 2009 through 25 October 2009

ER -

Data modeling and harmonization with OWL: Opportunities and lessons learned

Abstract

Keywords

ASJC Scopus subject areas

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Cite this