Combining cloud and Git tools in a research data management strategy for team science
In project management of collaborative research projects, there is an increasing demand for an information and communication technology (ICT) infrastructure because people are distributed in time and space, including a safe and legal data sharing infrastructure. Data managers want to foster the prod...
Sábháilte in:
| Foilsithe in: | Bausteine Forschungsdatenmanagement |
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| Príomhchruthaitheoirí: | , |
| Formáid: | Artikel (Zeitschrift) |
| Teanga: | Gearmáinis |
| Foilsithe / Cruthaithe: |
2026
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| Ábhair: | |
| Rochtain ar líne: | Rochtain ar líne |
| Clibeanna: |
Níl clibeanna ann, Bí ar an gcéad duine le clib a chur leis an taifead seo!
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| Achoimre: | In project management of collaborative research projects, there is an increasing demand for an information and communication technology (ICT) infrastructure because people are distributed in time and space, including a safe and legal data sharing infrastructure. Data managers want to foster the production of FAIR data by implementing best research data management (RDM) practices. In practice, the use of a cloud service is the easiest to implement, but shared folders tend to become huge and unorganised, which greatly limits the findability and reuse of the shared data. In order for data managers to regularly monitor activities on the shared folder, they need a better version control system than what cloud systems provide.
Here we present a strategy where the data manager uses the power of Git on a local copy of the shared folder. By spotting new and modified files, they can intervene very early and pro-actively to keep files organised, produce useful metadata, or publish data on behalf of the researchers. In particular, the data manager can move large files outside of the data synchronised on the researchers’ computers. This strategy was successfully implemented in two projects that collect relatively small datasets. Because most of the collected data is available and organised, publication and archival of the whole data can be performed by the data manager, potentially making this data FAIR during and after the project. |
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| ISSN: | 2626-7489 |
| DOI: | 10.17192/bfdm.2026.1.8721 |