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Systems Engineering
Article . 2023 . Peer-reviewed
License: CC BY NC
Data sources: Crossref
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https://dx.doi.org/10.48550/ar...
Article . 2022
License: CC BY
Data sources: Datacite
DBLP
Article . 2023
Data sources: DBLP
DBLP
Preprint . 2022
Data sources: DBLP
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Driving digital engineering integration and interoperability through semantic integration of models with ontologies

Authors: Daniel Dunbar; Thomas J. Hagedorn; Mark R. Blackburn; John E. Dzielski; Steven Hespelt; Benjamin Kruse; Dinesh Verma; +1 Authors

Driving digital engineering integration and interoperability through semantic integration of models with ontologies

Abstract

Abstract Engineered solutions are becoming more complex and multi‐disciplinary in nature. This evolution requires new techniques to enhance design and analysis tasks that incorporate data integration and interoperability across various engineering tool suites spanning multiple domains at different abstraction levels. Semantic web technologies (SWT) offer data integration and interoperability benefits as well as other opportunities to enhance reasoning across knowledge represented in multiple disparate models. This paper introduces the digital engineering framework for integration and interoperability (DEFII) for incorporating SWT into engineering design and analysis tasks. The framework includes three notional interfaces for interacting with ontology‐aligned data. It also introduces a novel model interface specification diagram (MISD) that provides a tool‐agnostic model representation enabled by SWT that exposes data stored for use by external users through standards‐based interfaces. Use of the framework results in a tool‐agnostic authoritative source of truth spanning the entire project, system, or mission.

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Keywords

FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    39
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
39
Top 10%
Top 10%
Top 1%
Green
hybrid