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ENHANCED FINDABILITY AND REUSABILITY OF ENGINEERING DATA BY CONTEXTUAL METADATA

Published online by Cambridge University Press:  19 June 2023

Osman Altun ,
Pooya Oladazimi ,
Max Leo Wawer ,
Selina Raumel ,
Marc Wurz ,
Khemais Barienti ,
Florian Nürnberger ,
Roland Lachmayer ,
Iryna Mozgova  and
Oliver Koepler
...Show all authors
Osman Altun*
Affiliation:
Leibniz University Hannover, Institute of Product Development
Pooya Oladazimi
Affiliation:
Leibniz Information Centre of Science and Technology University Library
Max Leo Wawer
Affiliation:
Leibniz University Hannover, Institute of Product Development
Selina Raumel
Affiliation:
Leibniz University Hannover, Institute of Micro Production Technology
Marc Wurz
Affiliation:
Leibniz University Hannover, Institute of Micro Production Technology
Khemais Barienti
Affiliation:
Leibniz University Hannover, Institut für Werkstoffkunde (Materials Science)
Florian Nürnberger
Affiliation:
Leibniz University Hannover, Institut für Werkstoffkunde (Materials Science)
Roland Lachmayer
Affiliation:
Leibniz University Hannover, Institute of Product Development
Iryna Mozgova
Affiliation:
Paderborn University, Data management in mechanical engineering
Oliver Koepler
Affiliation:
Leibniz Information Centre of Science and Technology University Library
Sören Auer
Affiliation:
Leibniz Information Centre of Science and Technology University Library
*
Altun, Osman, Leibniz University Hannover, Germany, altun@ipeg.uni-hannover.de

Abstract

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Complex research problems are increasingly addressed by interdisciplinary, collaborate research projects generating large amounts of heterogeneous amounts of data. The overarching processing, analysis and availability of data are critical success factors for these research efforts. Data repositories enable long term availability of such data for the scientific community. The findability and therefore reusability strongly builds on comprehensive annotations of datasets stored in repositories. Often generic metadata schema are used to annotate data. In this publication we describe the implementation of discipline specific metadata into a data repository to provide more contextual information about data. To avoid extra workload for researchers to provide such metadata a workflow with standardised data templates for automated metadata extraction during the ingest process has been developed. The enriched metadata are in the following used in the development of two repository plugins for data comparison and data visualisation. The added values of discipline-specific annotations and derived search features to support matching and reusable data is then demonstrated by use cases of two Collaborative Research Centres (CRC 1368 and CRC 1153).

Keywords

FAIR DataResearch Data ManagementKnowledge managementInformation managementProject management
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1635 - 1644
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), 2023. Published by Cambridge University Press

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