Use of Semantic Web Technologies to Enable System Level Verification in Multi-Disciplinary Models

Daniel Dunbar, Thomas Hagedorn, Mark Blackburn, Dinesh Verma

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    3 Scopus citations

    Abstract

    Integration of data from multiple sources into a single, project wide view is a necessity to keep up with increasing complexity and transdisciplinary considerations in engineering projects. Semantic Web Technologies (SWT) provide a unique way of linking and reasoning upon data from disparate sources to gain insights on the data viewed as a whole. By ingesting project data into a tool-agnostic repository and applying targeted reasoning, SWT can be used to perform system level verification tasks, such as providing a Key Performance Indicator (KPI) of completeness that gives project design and status insights to key stakeholders. This paper reports research creating a Semantic System Verification Layer (SSVL) as an extension to an existing Digital Engineering framework that utilizes SWT. This process and procedure are applied to a relevant use case to demonstrate and clarify the functions.

    Original languageEnglish
    Title of host publicationMoving Integrated Product Development to Service Clouds in the Global Economy - Proceedings of the 21st ISPE Inc. International Conference on Concurrent Engineering, CE 2014
    EditorsBryan R. Moser, Bryan R. Moser, Pisut Koomsap, Josip Stjepandic
    Pages63-72
    Number of pages10
    ISBN (Electronic)9781643683386
    DOIs
    StatePublished - 31 Oct 2022
    Event29th ISTE International Conference on Transdisciplinary Engineering, TE 2022 - Cambridge, United States
    Duration: 5 Jul 20228 Jul 2022

    Publication series

    NameAdvances in Transdisciplinary Engineering
    Volume28
    ISSN (Print)2352-751X
    ISSN (Electronic)2352-7528

    Conference

    Conference29th ISTE International Conference on Transdisciplinary Engineering, TE 2022
    Country/TerritoryUnited States
    CityCambridge
    Period5/07/228/07/22

    Keywords

    • digital engineering
    • knowledge representation
    • model validation and verification
    • model-based systems engineering
    • ontologies
    • semantic web

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