Workflow Provenance Records for Replicable Genomic Processing
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Solution Overview
Problem
Existing bioinformatics systems lack a comprehensive mechanism to efficiently store and replicate the execution details of computational workflows for processing genomic information, particularly in a modular and shareable format that allows for inspection and replication of processing steps.
Innovation Solution
A system is developed to generate a provenance record that includes an input component, workflow component, and record component, which facilitates the storage and aggregation of information related to computational workflows, enabling the replication and inspection of processing steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive tracking of computational workflow executions is implemented, then provenance information completeness is improved, but system complexity increases
Solution Approach 1:
The system segments the provenance tracking into distinct components: workflow definitions, computational modules, execution records, and provenance graphs. Each component handles specific aspects of tracking, making the overall complex task manageable and modular. The provenance graph itself is segmented into nodes representing workflows, modules, and data, connected by edges representing execution relationships.
Solution Approach 2:
The system introduces an intermediary provenance graph structure that mediates between the computational workflow execution and the stored provenance information. This graph acts as a bridge, automatically capturing execution details and transforming them into structured provenance records without requiring direct complex tracking throughout the entire workflow.
2Ease of manufacture
If modular and shareable storage format for workflow executions is implemented, then ease of replication is improved, but data structure complexity increases
Solution Approach 1:
The provenance record structure is designed with universal components that can represent different types of computational workflows and modules through a common schema. The standardized format with fields for workflow definitions, module parameters, inputs, outputs, and execution metadata enables the same structure to accommodate diverse bioinformatics operations while maintaining consistency and shareability.
Solution Approach 2:
The system uses parameterized templates for provenance records where specific fields can be dynamically configured based on the computational module type. This allows the data structure to adapt to different workflow needs while maintaining a consistent overall framework, reducing the need for multiple specialized storage formats.
3Ease of operation
If aggregation of provenance information is implemented, then information accessibility is improved, but processing time increases
Solution Approach 1:
The system performs preliminary aggregation of provenance information during the workflow execution itself, rather than after the fact. Execution records are captured and integrated into the provenance graph in real-time as computational modules execute, so that when queries are made later, the aggregated information is already ready and indexed for quick retrieval.
Solution Approach 2:
The system implements feedback mechanisms where execution metadata is continuously fed back into the provenance graph structure during workflow runs. This ongoing feedback loop allows the provenance information to be dynamically updated and aggregated as workflows execute, making the information immediately accessible for analysis and replication without requiring separate batch processing steps.
Data Source
AI summary
System and method for generating a provenance record for processing information in accordance with a computational workflow are disclosed. Exemplary implementations may: store workflow definitions and computational modules; receive user entry or selection indicating a first computational workflow and a first input information set; processing the first input information set in accordance with the first computational workflow to generate a first output information set; determine provenance information for processing the first input information set in accordance with the first computational workflow; aggregating the provenance information to generate a provenance record; outputting or storing the provenance record; and/or other exemplary implementations.