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Overview DataPLANT
2023-11-14

MibiNet connection to NFDIs


Data Stewardship between DataPLANT and the community

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Annotated Research Context (ARC)

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Your entire investigation in a single unified bag


You can store your ARC in the DataHUB

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ARCs are versioned

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You can invite collaborators

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Collaborate and contribute

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Reuse data in ARCs

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Publish your ARC

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ARC as single-entry point

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From ARC to repositories

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Moving from paper to data publications

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Publish your ARC, get a DOI

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Metadata templates

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Facilities and labs can define their common workflows as templates


Validate & publish

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Weil, H.L., Schneider, K., et al. (2023), PLANTdataHUB: a collaborative platform for continuous FAIR data sharing in plant research. Plant J. https://doi.org/10.1111/tpj.16474


Learning from Open-Source-Software development

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Data analysis and workflows

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Weil, H.L., Schneider, K., et al. (2023), PLANTdataHUB: a collaborative platform for continuous FAIR data sharing in plant research. Plant J. https://doi.org/10.1111/tpj.16474


Galaxy integration: Extra value for plant research

  • Full ARC compatibility
  • Automated metadata generation
  • Specialized tools and workflows for ‘omics processing and analysis
  • Public repository compatibility
  • Galaxy teaching resource for data analysis

Enabling platforms

  • Streamlined exchange of (meta)data
  • Communication and project management


Streamlined data exchange


Meet your collaborators in an ARC


Project management

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Weil, H.L., Schneider, K., et al. (2023), PLANTdataHUB: a collaborative platform for continuous FAIR data sharing in plant research. Plant J. https://doi.org/10.1111/tpj.16474


DataPLAN – a DataPLANT DMP generator

Zhou et al. (2023), DataPLAN: a web-based data management plan generator for the plant sciences, bioRxiv 2023.07.07.548147; doi: https://doi.org/10.1101/2023.07.07.548147

https://dmpg.nfdi4plants.org

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Everything is a file

DataPLANT employs a data-centric approach to RDM

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No technical lock-in

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(Meta)data transparency with tool assistance but no technical lock-in


The ARC ecosystem

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What does an ARC look like?

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ARCs store experimental data

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Computations can be run inside ARCs

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ARCs come with comprehensive metadata

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ARC builds on standards

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  • RO-Crate: standardized exchange
  • ISA: structured, machine-readable metadata
  • CWL: reproducible, re-usable data analysis
  • Git: version control

https://isa-tools.org/ | https://www.commonwl.org/ https://www.researchobject.org/ro-crate/ | https://git-scm.com