BioHackEU25 report: Towards a Robust Validation Service for Data and Metadata in ARC RO-Crates

Abstract

Robust validation of both research data and its accompanying metadata is essential for ensuring adherence to FAIR principles. Current approaches often handle these aspects separately, hindering a holistic quality assessment. Building upon previous BioHackathon work establishing ARCs (Annotated Research Context) as RO-Crates (ARC RO-Crate), we aim to develop and demonstrate an integrated validation strategy for FAIR digital objects. It distinguishes between validating the metadata descriptor and the payload data files.For the metadata descriptor, validation will ensure structural and semantic compliance to the base RO-Crate specification and the ARC-ISA family of RO-Crate profiles, using and extending the RO-Crate validator tool.For the payload data files, validation targets the actual content, since data files often require domain-specific structural and value constraints, which requires explicit schema definitions. For this, we will integrate Frictionless for checking data content against community standards (e.g. MIAPPE, as demonstrated in the HORIZON project AGENT). Crucially, this project will also explore mechanisms for specifying expected data structures’ requirements within the ARC RO-Crate itself. This aims to provide a more self-contained description of data, investigating how such internal requirements can be linked to data validation frameworks, complementing the crate’s metadata validation.The overall goal is to provide a powerful, holistic validation mechanism for ARC RO-Crates, enhancing their reliability, trustworthiness, and FAIRness. A MIAPPE-compliant plant phenomics dataset will serve as a use case. This integrated validation approach aims to streamline quality control for researchers and will be packaged as a deployable microservice, offering broad applicability across diverse research workflows.

Plant phenotyping relevance

ARC RO-Crateのデータ・メタデータ検証サービスを開発する研究で、MIAPPE準拠の植物フェノミクスデータセットを具体的ユースケースとして扱う。植物表現型データの再利用可能な検証ツール／ワークフローが中心である。

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