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Methodological Guidance for Engineering Knowledge Representation Using Semantic Web Technologies.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Methodological Guidance for Engineering Knowledge Representation Using Semantic Web Technologies./
Author:	Dunbar, Daniel.
Description:	1 online resource (38 pages)
Notes:	Source: Masters Abstracts International, Volume: 83-02.
Contained By:	Masters Abstracts International83-02.
Subject:	Engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28496220click for full text (PQDT)
ISBN:	9798534672473

Methodological Guidance for Engineering Knowledge Representation Using Semantic Web Technologies.
Dunbar, Daniel.

Methodological Guidance for Engineering Knowledge Representation Using Semantic Web Technologies. - 1 online resource (38 pages)

Source: Masters Abstracts International, Volume: 83-02.

Thesis (Master's)--Stevens Institute of Technology, 2021.

Includes bibliographical references

This paper describes a methodological approach that uses semantic technologies to integrate modeling data and associated information across domains into a centralized data store, enabling automated reasoning, connection of data despite disparate sources, and tool interoperability without the requirement of extensive tool-to-tool services. The methodology and the associated implementation use ontologies as a means for knowledge representation and take advantage of semantic technologies, which have been demonstrated to be tool agnostic, extensible, and capable of automated reasoning and AI-based applications, such as Digital Assistants.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798534672473Subjects--Topical Terms:

586835
Engineering.
Subjects--Index Terms:

Digital engineeringIndex Terms--Genre/Form:

542853
Electronic books.

Methodological Guidance for Engineering Knowledge Representation Using Semantic Web Technologies.
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500 $a Source: Masters Abstracts International, Volume: 83-02.
500 $a Advisor: Blackburn, Mark.
502 $a Thesis (Master's)--Stevens Institute of Technology, 2021.
504 $a Includes bibliographical references
520 $a This paper describes a methodological approach that uses semantic technologies to integrate modeling data and associated information across domains into a centralized data store, enabling automated reasoning, connection of data despite disparate sources, and tool interoperability without the requirement of extensive tool-to-tool services. The methodology and the associated implementation use ontologies as a means for knowledge representation and take advantage of semantic technologies, which have been demonstrated to be tool agnostic, extensible, and capable of automated reasoning and AI-based applications, such as Digital Assistants.
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538 $a Mode of access: World Wide Web
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773 0 $t Masters Abstracts International $g 83-02.
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