Researchers at the National Center for Genomic Analysis (CNAG), located at the Barcelona Science Park of the University of Barcelona (PCB-UB), have developed ClarID, an identifier specification designed to facilitate the interpretation of subject and biological sample identifiers in biomedical research workflows. The study, published in the Journal of Biomedical Semantics, provides structured, human-readable identifiers that encode selected metadata and can be used alongside existing identifiers.

In biomedical research, one of the most common practical challenges is linking subject and biosample identifiers to their associated metadata. Subject and biosample identifiers are generally designed to be unique rather than informative. As a result, researchers often need to consult external metadata tables to understand the context of a sample, such as its tissue, assay, or associated disease.

Although some large-scale projects and domain-specific initiatives use structured identifiers, these systems are typically tailored to the original context for which they were created. To address this practical need, the Biomedical Genomics Group at CNAG developed ClarID. Rather than replacing persistent identifiers such as UUIDs, ClarID is intended to be used alongside them.

“The motivation for creating ClarID came from a very practical need,” explains Dr. Manuel Rueda, researcher at CNAG and first author of the study. “When working with large cohorts, we often had to consult external metadata tables simply to understand what a sample or subject identifier referred to. ClarID was designed as a simple and automatable way to add useful contextual information to identifiers while retaining persistent identifiers such as UUIDs.”

Two complementary formats to meet different research needs

The first is a human-readable format, with fields that vary depending on whether the identifier represents a subject or a biosample. In the case of biosamples, the identifier includes the project, species, subject ID, tissue, sample type, assay, condition, timepoint, and duration, with optional fields for batch and replicate information. Subject identifiers use a different structure that includes the study, subject ID, subject type, condition, sex, and age group.

The second format, known as a stub, is a more compact representation designed for situations where shorter identifiers are useful, such as filenames, analysis pipelines, labels, or QR code workflows.

ClarID is accompanied by ClarID-Tools, an open-source command-line implementation that enables users to generate, decode, and validate identifiers from tabular metadata files using a YAML-based codebook. The toolkit also supports schema validation and QR code generation, making it easier to integrate ClarID into research data workflows.

As a demonstration, the authors applied ClarID-Tools to public metadata from the Genomic Data Commons, generating identifiers for 113,760 subject-level clinical records across 86 studies and 4,255 biospecimen records from the TARGET-AML project. The associated code, examples, and reproducible materials are available through the ClarID-Tools repository and a linked Google Colab notebook.

Overall, ClarID is not intended to encode all metadata or replace laboratory information management systems, metadata repositories, or persistent identifiers. Instead, it provides a lightweight companion identifier that can improve readability, support metadata curation, and facilitate day-to-day data management in biomedical and life sciences projects.

The specification uses a configurable codebook, allowing projects to adapt it to their own terminology and requirements.

» Article of reference: Rueda, M., Gut, I.G. ClarID: a human-readable and compact identifier specification for biomedical metadata integration. Journal of Biomedical Semantics 17, 9 (2026). DOI: https://doi.org/10.1186/s13326-026-00349-6

» Link to the news: CNAG website [+]