Structuring research methods and data with the research object model: genomics workflows as a case study.

Area of Science:

• Bioinformatics
• Computational Biology
• Data Science

Background:

• Biomedical research faces challenges in integrating complex data for molecular mechanism studies.
• Reproducibility requires clear annotation and preservation of computational experiment methods.
• A structured approach to aggregating and annotating experimental resources is needed.

Purpose of the Study:

• To explore a model for semantic description of workflow-centric Research Objects (ROs).
• To support the digital, structured aggregation and annotation of experimental resources.
• To provide necessary metadata for understanding and recreating experimental results.

Main Methods:

• Developed a workflow-centric Research Object (RO) model.
• Applied the RO model to a case study analyzing human metabolite variation using workflows.
• Ensured workflows followed Best Practices for workflow design.

Main Results:

• Demonstrated the application of the workflow-centric RO model in a bioinformatics case study.
• Enabled automatic querying of experimental data, linking hypotheses, workflows, and conclusions.
• Successfully answered questions about data input and conclusions drawn from specific workflows.

Conclusions:

• The workflow-centric RO model effectively aggregates and annotates bioinformatics experiment resources.
• This model facilitates retrieval of experimental conclusions within their context (hypothesis, workflows, data).
• The RO model is extendable and can be adopted by other systems.