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ro-crate-rs: Development of a Lightweight RO-Crate Rust Library for Automated Synthetic Biology

Burridge, M. S.; Ou, Z.; James, K.; Lim, J.; Buldum, G.; Finnigan, J.; Charnock, S. J.; Wipat, A.

2026-01-22 synthetic biology
10.64898/2026.01.22.701040 bioRxiv
Show abstract

Advances in laboratory automation and AI-driven experimental design have increased the scale and complexity of data generated in synthetic biology. Whilst biofoundries provide significant resources and infrastructure to execute these experiments, most laboratories rely on isolated automated instruments and software systems that operate as disconnected silos, producing heterogeneous data formats with little structured metadata. This fragmentation hinders data integration, reproducibility, and downstream computational workflows. A potential solution is RO-Crate, which offers a lightweight, extensible framework for packaging research data with machine-readable metadata, but existing tooling remains immature for automation-orientated, cloud-native, or high-throughput laboratory workflows. Here, we introduce ro-crate-rs, a new suite of tools centred on a performant Rust library for constructing, validating and packaging RO-Crates across diverse compute environments and automated hardware. The library enforces RO-Crate 1.1 constraints through strong typing while enabling flexible extensions, and is complemented by a Python API and CLI for interactive use and pipeline integration. We demonstrate this combined approach through a semi-automated Old Yellow Enzyme characterisation workflow, showing how RO-Crates can capture data and metadata across multiple independent instruments. Together, these tools provide a robust foundation for FAIR-compliant, automation-ready data management and enable reproducible reconstruction of experimental workflows even in non-biofoundry settings. Availabilityhttps://github.com/intbio-ncl/ro-crate-rs

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