brapi2arc

This API server allows researchers to submit phenotyping observations to a dataset stored as an Annotated Research Context (ARC). The ARC provides a standardized structure for capturing and sharing research data, enabling reproducibility and transparency in scientific investigations.

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Description

The brapi2arc tool is a powerful utility designed for BrAPI-enabled phenotyping applications, such as GridScore. It facilitates seamless data management by enabling users to export recorded observations directly to an Annotated Research Context (ARC). This functionality is crucial for researchers and data managers who require efficient data handling and integration within their workflows.

One of the key features of brapi2arc is its ability to import trial setups from a BrAPI server, ensuring that users can easily access and utilize existing trial configurations. This integration simplifies the process of managing phenotyping data and fosters collaboration among researchers.

Additionally, brapi2arc manages the deployment of the BrAPI server, allowing users to focus on their research without the complexities of server setup and maintenance. It also ensures that any changes made during the data export process are automatically committed back to the DataHUB from which the ARC originated. This feature enhances data integrity and traceability, making it easier for teams to maintain consistent and accurate datasets.

Key Features include:

  • Export Observations: Directly export recorded observations to an Annotated Research Context (ARC).
  • Import Trial Setup: Easily import trial configurations from a BrAPI server.
  • Automated Server Deployment: Simplifies the deployment of the BrAPI server for user convenience.
  • Automatic Data Commit: Automatically commits changes to the DataHUB from which the ARC originated.
  • Enhanced Data Integrity: Maintains consistency and accuracy of datasets throughout the research process.
    Overall, brapi2arc streamlines the interaction between BrAPI applications and ARCs, improving the efficiency of phenotyping research and data management.
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Programming language
  • Python 100%
License
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github.com

Participating organisations

Bioinformatics and Information Technology
Bioinformatics and Information Technology

Reference papers

Contributors

MF
Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK)

Member of community

BrAPI

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