<div class="csl-bib-body">
<div class="csl-entry">Weise, M., & Rauber, A. (2024). DBRepo: A Data Repository System for Research Data in Databases. In <i>2024 IEEE International Conference on Big Data (BigData)</i> (pp. 322–331). https://doi.org/10.1109/BigData62323.2024.10825401</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/209951
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dc.description.abstract
In the era of big data, research has become increasingly data-driven, with vast amounts of information being generated and analyzed to produce new insights and discoveries. This data deluge requires a combination of methods and technologies to store, process, share and preserve research data. With many of the world’s most valuable data being stored in relational databases where it evolves over time as new knowledge is gained and old knowledge invalidated, current repository systems fail to provide researchers with interfaces to conveniently work with this kind of data within their research environments. For this reason, we have developed DBRepo, an institutional data repository for research data in databases (DBRepo) supporting guidelines of the Working Group on Data Citation of the Research Data Alliance. The system has been in use at TU Wien for almost three years now and provides a variety of data science-related interfaces and can be integrated into many workflows and tools. Further, it assists researchers in depositing their datasets by suggesting the table schema (column names, data types, primary key constraints) and it addresses data interoperability issues by suggesting semantic concepts for dataset columns and units of measurements, where applicable. DBRepo is currently in use by six universities globally who use it as data store for hot and cold research data sets. In the paper, we describe their use-cases and provide lessons learned from the various deployments and workflows. Finally, we show how depositing research data into DBRepo increases the data’s visibility.
en
dc.language.iso
en
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dc.subject
Research Data Repositories
en
dc.subject
Relational Databases
en
dc.subject
Research Data Management
en
dc.title
DBRepo: A Data Repository System for Research Data in Databases
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.relation.isbn
979-8-3503-6248-0
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dc.relation.doi
10.1109/BigData62323.2024
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dc.description.startpage
322
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dc.description.endpage
331
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
2024 IEEE International Conference on Big Data (BigData)
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tuw.researchTopic.id
I4
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tuw.researchTopic.name
Information Systems Engineering
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E194-04 - Forschungsbereich Data Science
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tuw.publisher.doi
10.1109/BigData62323.2024.10825401
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dc.description.numberOfPages
10
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tuw.author.orcid
0000-0003-4216-302X
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tuw.author.orcid
0000-0002-9272-6225
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tuw.event.name
2024 IEEE International Conference on Big Data
en
tuw.event.startdate
15-12-2024
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tuw.event.enddate
18-12-2024
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Washington DC
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tuw.event.country
US
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tuw.event.presenter
Weise, Martin
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tuw.event.track
Multi Track
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wb.sciencebranch
Informatik
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wb.sciencebranch
Wirtschaftswissenschaften
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
5020
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wb.sciencebranch.value
90
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wb.sciencebranch.value
10
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.cerifentitytype
Publications
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item.languageiso639-1
en
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item.fulltext
no Fulltext
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item.openairetype
conference paper
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item.grantfulltext
restricted
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crisitem.author.dept
E194-04 - Forschungsbereich Data Science
-
crisitem.author.dept
E194-04 - Forschungsbereich Data Science
-
crisitem.author.orcid
0000-0003-4216-302X
-
crisitem.author.orcid
0000-0002-9272-6225
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering