New blog post about how to represent BiomarkerKB (https://biomarkerkb.org) in @bioregistry

📖 https://cthoyt.com/2025/08/22/bioregistry-and-biomarkerkb.html

Also useful for anyone else running a database in the life/natural sciences who might want to make it more findable and FAIR - please get in touch!

#PIDs #semanticweb #linkedopendata #linkeddata #bioregistry #curies #fair #fairdata #researchdatamanagement #rdm

BiomarkerKB

BiomarkerKB is a Common Fund Data Ecosystem (CFDE) sponsored project to develop a knowledgebase that will organize and integrate biomarker data from different public sources.

Data Standardization and Integration with the Bioregistry at Biocuration 2025

GitHub site for the Biopragmatics Stack

Biopragmatics Stack

The only sane way to deal with #CURIEs in code: Expand as early as possible and contract as late as possible.

Expand CURIEs in the input layer, as soon as you got the data from the outside world. Contract them in the output layer, just before you send the data back to the outside world.

Between the two, let your code be a CURIE-free zone, where the only identifiers are opaque full-length IRIs.

Life is too short to spend it dealing with CURIEs more than what’s absolutely necessary.

I re-implemented the Name-to-Things (N2T) ARK resolver using the `curies` Python package and wrote an explanation of how I did it here: https://cthoyt.com/2023/04/11/n2t-ark-resolver.html

Code available here: https://github.com/cthoyt/n2t-ark-resolver

#arks #pids #semanticweb #curies #uris

Re-implementing the N2T ARK Resolver

Archival Resource Keys (ARKs) are flavor of persistent identifiers like DOIs, URNs, and Handles that have the benefit of being free, flexible with what metadata gets attached, and natively able to resolve to web pages. Names to Things (N2T) implements a resolver for a variety of ARKs, so this blog post is about how that resolver can be re-implemented with the curies Python package.

Biopragmatics