ENHANCED FINDABILITY AND REUSABILITY OF ENGINEERING DATA BY CONTEXTUAL METADATA
Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nad
Author: Altun, Osman (1); Oladazimi, Pooya (2); Wawer, Max Leo (1); Raumel, Selina (3); Wurz, Marc (3); Barienti, Khemais (4); Nürnberger, Florian (4); Lachmayer, Roland (1); Mozgova, Iryna (5); Koepler, Oliver (2); Auer, Sören (2)
Series: ICED
Institution: 1: Leibniz University Hannover, Institute of Product Development;2: Leibniz Information Centre of Science and Technology University Library;3: Leibniz University Hannover, Institute of Micro Production Technology;4: Leibniz University Hannover, Institut f
Section: Design Methods
Page(s): 1635-1644
DOI number: https://doi.org/10.1017/pds.2023.164
ISBN: -
ISSN: -
Abstract
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 Data, Research Data Management, Knowledge management, Information management, Project management