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Knowledge Annotation within Research Data Management System for Oxygen-Free Production Technologies

Published online by Cambridge University Press:  26 May 2022

I. Mozgova ,
O. Altun ,
T. Sheveleva ,
A. Castro ,
P. Oladazimi ,
O. Koepler ,
R. Lachmayer  and
S. Auer
I. Mozgova*
Affiliation:
Leibniz Universität Hannover, Germany
O. Altun
Affiliation:
Leibniz Universität Hannover, Germany
T. Sheveleva
Affiliation:
Leibniz Information Centre of Science and Technology University Library, Germany
A. Castro
Affiliation:
Leibniz Information Centre of Science and Technology University Library, Germany
P. Oladazimi
Affiliation:
Leibniz Information Centre of Science and Technology University Library, Germany
O. Koepler
Affiliation:
Leibniz Information Centre of Science and Technology University Library, Germany
R. Lachmayer
Affiliation:
Leibniz Universität Hannover, Germany
S. Auer
Affiliation:
Leibniz Information Centre of Science and Technology University Library, Germany
*
mozgova@ipeg.uni-hannover.de

Abstract

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The comprehensive implementation of digital technologies in product manufacturing leads to changes in engineering processes and requires new approaches to data management. An important role belongs to the processes of organizing the collection, storage and reuse of research data obtained and used in the process of product, system or technology development, taking into account the FAIR data principles. This article describes a Research Data Management System for the organization of documentation and measurement requests in the research and development of new oxygen-free production technologies.

Keywords

research data managementknowledge managementsemantic modellingFAIR data principlesdesign support system
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 525 - 532
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), 2022.

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