Cargando…

OMEX metadata specification (version 1.2)

A standardized approach to annotating computational biomedical models and their associated files can facilitate model reuse and reproducibility among research groups, enhance search and retrieval of models and data, and enable semantic comparisons between models. Motivated by these potential benefit...

Descripción completa

Detalles Bibliográficos
Autores principales: Gennari, John H., König, Matthias, Misirli, Goksel, Neal, Maxwell L., Nickerson, David P., Waltemath, Dagmar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8560343/
https://www.ncbi.nlm.nih.gov/pubmed/34668356
http://dx.doi.org/10.1515/jib-2021-0020
Descripción
Sumario:A standardized approach to annotating computational biomedical models and their associated files can facilitate model reuse and reproducibility among research groups, enhance search and retrieval of models and data, and enable semantic comparisons between models. Motivated by these potential benefits and guided by consensus across the COmputational Modeling in BIology NEtwork (COMBINE) community, we have developed a specification for encoding annotations in Open Modeling and EXchange (OMEX)-formatted archives. This document details version 1.2 of the specification, which builds on version 1.0 published last year in this journal. In particular, this version includes a set of initial model-level annotations (whereas v 1.0 described exclusively annotations at a smaller scale). Additionally, this version uses best practices for namespaces, and introduces omex-library.org as a common root for all annotations. Distributing modeling projects within an OMEX archive is a best practice established by COMBINE, and the OMEX metadata specification presented here provides a harmonized, community-driven approach for annotating a variety of standardized model representations. This specification acts as a technical guideline for developing software tools that can support this standard, and thereby encourages broad advances in model reuse, discovery, and semantic analyses.