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

6 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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