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A Semantic Workbench for Editing, Querying, Navigating and Distributing Ontologies for Cognitive Manufacturing

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

Details

Original languageEnglish
Title of host publicationIECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE
Pages2767-2772
Number of pages6
ISBN (Electronic)978-1-7281-4878-6
ISBN (Print)978-1-7281-4879-3
DOIs
Publication statusPublished - 1 Oct 2019
Publication typeA4 Article in a conference publication
EventAnnual Conference of the IEEE Industrial Electronics Society -
Duration: 1 Jan 1900 → …

Publication series

NameAnnual Conference of the IEEE Industrial Electronics Society
ISSN (Print)1553-572X
ISSN (Electronic)2577-1647

Conference

ConferenceAnnual Conference of the IEEE Industrial Electronics Society
Period1/01/00 → …

Abstract

Manufacturing-oriented enterprises are investing in novel solutions to adapt their cyber and physical resources to the fast and, yet, unexpected changes of global industrial environment. One of the important trends is to work towards development of cognitive systems which are capable to process and analyze complex data using Artificial Intelligence (AI)-based tools and techniques. Therefore, cognition can be already viewed as a requirement for hyper-connected environments e.g., the factories of the future or the Internet of Things (IoT). In this context, there is a need to represent and store the data collected from machines in a format that can be understood and manipulated by both humans and machines. This is feasible by designing and implementing semantic models i.e., ontologies which, in turn, enable inferring implicit data of explicit knowledge, leading to cognition. Moreover, there is a need of granting the access to such information remotely and at system runtime. Within this conceptual article, the authors present a semantic workbench that was developed during a European project aiming at utilization of ontologies for knowledge representation and reasoning in industrial automation systems. Further, this research work proposes the encapsulation of semantic workbench as a service in order to be deployed in cloud-based platforms, hence, enabling remote access of authorized clients at system runtime. The proposed functionalities are also of critical importance in highly complex and distributed environments, like the IoT or industrial ecosystems.

Keywords

  • Ontologies, Semantics, Cognition, Manufacturing, Cloud computing, Production facilities, Industries, Cognitive manufacturing, industrial internet, knowledge representation, ontology, cloud-based systems

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