Meta-omics data and collection objects (MOD-CO): a conceptual schema and data model for processing sample data in...

Area of Science:

• Molecular biology
• Bioinformatics
• Data science

Background:

• Advanced molecular meta-omics techniques enable detailed analysis of historic and environmental samples.
• Current data structures and standards primarily focus on data exchange and publication, neglecting operational and management aspects.
• There is a growing need for comprehensive data schemas to support meta-omics research.

Purpose of the Study:

• To introduce the Meta-omics Data and Collection Objects (MOD-CO) schema, a new data structure for meta-omics research.
• To provide a hierarchical organization for concepts describing collection samples, products, and data objects.
• To focus on object trait descriptions and operational aspects for laboratory information management.

Main Methods:

• Development of the MOD-CO schema with hierarchical organization.
• Inclusion of 653 concepts and 1810 predefined concept values.
• Publication in Semantic Media Wiki with interlinked pages and grouping into 37 collections.
• Application of the DiversityDescriptions SQL database for schema setup and testing.

Main Results:

• The MOD-CO schema version 1.0 has been established.
• It includes a detailed ontology for meta-omics data and collection objects.
• The schema is published via a Semantic Media Wiki and supported by a database application.
• MOD-CO can serve as a backbone for R&D laboratory information management systems.

Conclusions:

• The MOD-CO schema provides a robust framework for managing meta-omics data and collection objects.
• It addresses the limitations of existing schemas by incorporating operational details.
• MOD-CO facilitates standardized data handling and enhances the capabilities of laboratory information management systems.