Annotated Research Context (ARC) – Specification for FAIR Research Data
Overview
The Annotated Research Context (ARC) is a specification for organizing, documenting, and sharing research data together with its metadata, experimental context, computational workflows, and analysis results. Developed within the DataPLANT community under the NFDI4Plants initiative, ARC provides a structured approach to managing research data throughout its lifecycle.
An ARC is designed as a self-contained, human-readable and machine-actionable research package. It supports collaboration, preservation, reproducibility, and reuse by keeping data and the context required to interpret and process it together.
Key capabilities include:
- Structured research documentation: Organize investigation-level, study-level, and assay-level metadata.
- Data and metadata association: Keep measurements, input materials, data files, and contextual descriptions connected.
- Workflow documentation: Describe computational workflows and link them to their inputs and outputs.
- Provenance and version history: Use Git-based version control to track changes to the research package.
- Reproducibility: Preserve relevant data, metadata, workflow descriptions, and analysis outputs together.
- Interoperability: Build on established metadata models and workflow specifications to facilitate exchange with other research data systems.
- FAIR data management: Support data that is findable, accessible under defined conditions, interoperable, and reusable.