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REPRESENTATION AND APPLICATION OF DIGITAL STANDARDS USING KNOWLEDGE GRAPHS

Published online by Cambridge University Press:  27 July 2021

Janosch Luttmer ,
Dominik Ehring ,
Robin Pluhnau  and
Arun Nagarajah
Janosch Luttmer*
Affiliation:
University Duisburg-Essen
Dominik Ehring
Affiliation:
University Duisburg-Essen
Robin Pluhnau
Affiliation:
University Duisburg-Essen
Arun Nagarajah
Affiliation:
University Duisburg-Essen
*
Luttmer, Janosch, University Duisburg-Essen, Institute of Product Engineering, Germany, janosch.luttmer@uni-due.de

Abstract

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Standards are an important source of knowledge in product development. Due to the increasing digitization of the product development process, standard development organizations aim to develop machine-actionable standards that automatically enforce operations in output devices. However, the current representation format in PDF or XML does not meet the requirements of machine-actionable standards. This paper examines existing approaches towards the representation of XML data in knowledge graphs and their transferability towards the domain of digital standards. Based on these approaches, the paper aims to develop and validate a concept for transferring standard content from XML format to a graph-based representation, using the example of formulas. For this purpose, a concept for the automatic identification, extraction and modeling of formulas will be presented. Afterwards, the concept is validated using the example of DIN ISO 281 whereas a chatbot application serves as conversational user interface. It is proven, that knowledge graphs are suitable for the representation of machine-actionable standard content. Future work will investigate the abstraction towards a general approach as well as further information objects of standards.

Keywords

StandardsConceptual designKnowledge graphsKnowledge managementSemantic data processing
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 2551 - 2560
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

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