<div class="csl-bib-body">
<div class="csl-entry">Sabou, R. M., Kovalenko, O., & Novak, P. (2016). Semantic Modelling and Acquisition of Engineering Knowledge. In <i>Semantic Web for Intelligent Engineering Applications</i>. Springer International Publishing Switzerland. https://doi.org/10.1007/978-3-319-41490-4_5</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/29324
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dc.description.abstract
Ontologies are key Semantic Web technologies (SWTs) that provide
means to formally and explicitly represent domain knowledge in terms of key domain
concepts and their relations. Therefore, the creation of intelligent engineering
applications (IEAs) that rely on SWTs depends on the creation of a suitable ontology
that semantically models engineering knowledge and the representation of engineering
data in terms of this ontology (i.e., through a knowledge acquisition process).
The tasks of semantic modelling and acquisition of engineering knowledge
are, however, complex tasks that rely on specialized skills provided by a knowledge
engineer and can therefore be daunting for those SWT adopters that do not possess
this skill set. This chapter aims to support these SWT adopters by summing up essential
knowledge for creating and populating ontologies including: ontology engineering
methodologies and methods for assessing the quality of the created ontologies.
The chapter provides examples of concrete engineering ontologies, and
classifies these engineering ontologies in a framework based on the Product-Process-
Resource abstraction. The chapter also contains examples of best practices for
modelling common situations in the engineering domain using ontology design patterns,
and gives an overview of the current tools that engineers can use to lift engineering
data stored in legacy formats (such as, spreadsheets, XML files, and databases,
etc.) to a semantic representation.
en
dc.publisher
Springer International Publishing Switzerland
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dc.subject
ontology modelling
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dc.subject
ontology engineering methodologies
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dc.subject
ontology evaluation
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dc.subject
classification of engineering ontologies
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dc.subject
ontology design patterns
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dc.subject
ontology population
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dc.title
Semantic Modelling and Acquisition of Engineering Knowledge
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dc.type
Buchbeitrag
de
dc.type
Book Contribution
en
dc.relation.publication
Semantic Web for Intelligent Engineering Applications
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dc.relation.isbn
978-3-319-41490-4
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dc.relation.doi
10.1007/978-3-319-41490-4
-
dc.type.category
Edited Volume Contribution
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tuw.booktitle
Semantic Web for Intelligent Engineering Applications
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tuw.peerreviewed
true
-
tuw.relation.publisher
Springer Cham
-
tuw.researchTopic.id
I6
-
tuw.researchTopic.id
I4
-
tuw.researchTopic.name
Business Informatics
-
tuw.researchTopic.name
Distributed and Parallel Systems
-
tuw.researchTopic.value
50
-
tuw.researchTopic.value
50
-
tuw.publication.orgunit
E194-01 - Forschungsbereich Information und Software Engineering
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tuw.publisher.doi
10.1007/978-3-319-41490-4_5
-
dc.description.numberOfPages
32
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wb.sciencebranch
Informatik
-
wb.sciencebranch.oefos
1020
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item.fulltext
no Fulltext
-
item.openairecristype
http://purl.org/coar/resource_type/c_3248
-
item.cerifentitytype
Publications
-
item.openairetype
book part
-
item.grantfulltext
none
-
crisitem.author.dept
E194-04 - Forschungsbereich E-Commerce
-
crisitem.author.dept
E188 - Institut für Softwaretechnik und Interaktive Systeme
-
crisitem.author.dept
E188 - Institut für Softwaretechnik und Interaktive Systeme
-
crisitem.author.orcid
0000-0001-9301-8418
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering