Towards FAIR and federated data ecosystems for interdisciplinary research

Sebastian Beyvers, Jannis Schlegel, Lukas Brehm, Maria Hansen, Alexander Goesmann, Frank Förster

Open source

DOI: 10.1371/journal.pcbi.1013806
Published: 2026-02-13
Container: PLOS Computational Biology
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pcbi.1013806,
  title = {Towards FAIR and federated data ecosystems for interdisciplinary research},
  author = {Sebastian Beyvers and Jannis Schlegel and Lukas Brehm and Maria Hansen and Alexander Goesmann and Frank Förster},
  year = {2026},
  journal = {PLOS Computational Biology},
  doi = {10.1371/journal.pcbi.1013806},
  url = {https://doi.org/10.1371/journal.pcbi.1013806}
}

RIS

TY  - JOUR
TI  - Towards FAIR and federated data ecosystems for interdisciplinary research
AU  - Sebastian Beyvers
AU  - Jannis Schlegel
AU  - Lukas Brehm
AU  - Maria Hansen
AU  - Alexander Goesmann
AU  - Frank Förster
PY  - 2026
JO  - PLOS Computational Biology
DO  - 10.1371/journal.pcbi.1013806
UR  - https://doi.org/10.1371/journal.pcbi.1013806
ER  -

APA

Beyvers, S., Schlegel, J., Brehm, L., Hansen, M., Goesmann, A., & Förster, F. (2026). Towards FAIR and federated data ecosystems for interdisciplinary research. PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1013806

Source records

crossref · retrieved 2026-09-25T01:58:19.285Z