libOmexMeta: enabling semantic annotation of models to support FAIR principles

Area of Science:

• Computational Biology
• Bioinformatics
• Systems Biology

Background:

• The increasing complexity of biosimulation models necessitates improved methods for understanding, finding, sharing, and reproducing them.
• Current challenges include diverse model and tool programming languages, hindering standardization.
• Consistent model annotation is crucial for addressing these challenges.

Purpose of the Study:

• To introduce a novel, open-source, cross-platform software library for semantic model annotation.
• To provide a language-independent solution for annotating biosimulation models.
• To facilitate better model understanding, findability, shareability, and reproducibility.

Main Methods:

• Development of libOmexMeta, a software library based on community consensus.
• Implementation of a language-independent approach to semantic annotation.
• Leveraging open-source and cross-platform principles.

Main Results:

• Introduction of libOmexMeta, an open-source, cross-platform library for semantic annotation.
• The library supports consistent annotation across diverse modeling languages.
• Enhanced model findability, shareability, and reproducibility are anticipated.

Conclusions:

• libOmexMeta offers a standardized solution for semantic annotation in biosimulation.
• The library promotes interoperability and reproducibility in computational biology.
• This tool addresses a critical need for managing complex biological models.