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Integration of Well‐Formed Semantic Mapping to Extract System Optimization Information.

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Title: Integration of Well‐Formed Semantic Mapping to Extract System Optimization Information.
Authors: Eddy, Douglas1 (AUTHOR) dceddy@umass.edu, Dunbar, Daniel2 (AUTHOR) ddunbar1@stevens.edu, Blackburn, Mark2 (AUTHOR), Grosse, Ian1 (AUTHOR) grosse@engin.umass.edu, Hagedorn, Thomas2 (AUTHOR) thagedor@stevens.edu
Source: Systems Engineering. Sep2026, Vol. 29 Issue 5, p823-841. 19p.
Subjects: Semantic Web, Modeling languages (Computer science), Multiple criteria decision making, Digital technology, Prediction models, Concept mapping, Mathematical optimization, Design science
Abstract: Systems that are typically modeled within SysML are complex and not easily represented in their full semantic context. Furthermore, model complexity poses challenges to rapid and optimal decision making early in a system development process without significant trial and error. There are some cases where representative data can be obtained to characterize a complex system's overall performance. For such cases, this work introduces a method grounded in the fundamentals of rigorous decision‐based design principles by its integration within a semantic Interoperability and Integration Framework (IoIF) that interfaces with SysML for digital engineering of complex system models. Salient features include simplified formulation of SysML model information to conform to fundamental principles. This resulting Best System Selection (BestSys) method utilizes data that represents any system‐of‐interest along with its requirements information within SysML to identify the best option. The method also constructs a surrogate model from the data to find a potential better solution in the trade space not located at a data point. The workflow further maps that system's information within IoIF in a way that may enable SPARQL queries and consistently meaningful visualizations. [ABSTRACT FROM AUTHOR]
Copyright of Systems Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 196417803
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Integration of Well‐Formed Semantic Mapping to Extract System Optimization Information.
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  Data: <searchLink fieldCode="AR" term="%22Eddy%2C+Douglas%22">Eddy, Douglas</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> dceddy@umass.edu</i><br /><searchLink fieldCode="AR" term="%22Dunbar%2C+Daniel%22">Dunbar, Daniel</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> ddunbar1@stevens.edu</i><br /><searchLink fieldCode="AR" term="%22Blackburn%2C+Mark%22">Blackburn, Mark</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Grosse%2C+Ian%22">Grosse, Ian</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> grosse@engin.umass.edu</i><br /><searchLink fieldCode="AR" term="%22Hagedorn%2C+Thomas%22">Hagedorn, Thomas</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> thagedor@stevens.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Systems+Engineering%22">Systems Engineering</searchLink>. Sep2026, Vol. 29 Issue 5, p823-841. 19p.
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  Data: <searchLink fieldCode="DE" term="%22Semantic+Web%22">Semantic Web</searchLink><br /><searchLink fieldCode="DE" term="%22Modeling+languages+%28Computer+science%29%22">Modeling languages (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Multiple+criteria+decision+making%22">Multiple criteria decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+technology%22">Digital technology</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Concept+mapping%22">Concept mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Design+science%22">Design science</searchLink>
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  Data: Systems that are typically modeled within SysML are complex and not easily represented in their full semantic context. Furthermore, model complexity poses challenges to rapid and optimal decision making early in a system development process without significant trial and error. There are some cases where representative data can be obtained to characterize a complex system's overall performance. For such cases, this work introduces a method grounded in the fundamentals of rigorous decision‐based design principles by its integration within a semantic Interoperability and Integration Framework (IoIF) that interfaces with SysML for digital engineering of complex system models. Salient features include simplified formulation of SysML model information to conform to fundamental principles. This resulting Best System Selection (BestSys) method utilizes data that represents any system‐of‐interest along with its requirements information within SysML to identify the best option. The method also constructs a surrogate model from the data to find a potential better solution in the trade space not located at a data point. The workflow further maps that system's information within IoIF in a way that may enable SPARQL queries and consistently meaningful visualizations. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Systems Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1002/sys.70054
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        Text: English
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      – SubjectFull: Semantic Web
        Type: general
      – SubjectFull: Modeling languages (Computer science)
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      – SubjectFull: Multiple criteria decision making
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      – SubjectFull: Digital technology
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      – SubjectFull: Prediction models
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      – SubjectFull: Concept mapping
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      – SubjectFull: Mathematical optimization
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      – SubjectFull: Design science
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      – TitleFull: Integration of Well‐Formed Semantic Mapping to Extract System Optimization Information.
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              M: 09
              Text: Sep2026
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              Y: 2026
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