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Managing and Documenting Legacy Scientific Workflows.

Ruben Acuña, Jacques Chomilier, Zoé Lacroix

Journal of Integrative Bioinformatics

|December 18, 2015

Summary

This summary is machine-generated.

This study introduces the Workflow Instrumentation for Structure Extraction (WISE) method to automatically generate structural skeletons from poorly documented, legacy scientific workflows written in Python. WISE processes ad-hoc workflows without requiring prior formalization and analyzes external tool calls.

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Area of Science:

Computer Science
Bioinformatics
Scientific Computing

Background:

Legacy scientific workflows, often developed over many years using scripting languages, present significant maintenance challenges due to poor documentation.
Cross-disciplinary research frequently encounters difficulties in managing and understanding these complex, existing computational pipelines.

Purpose of the Study:

To present a novel method, Workflow Instrumentation for Structure Extraction (WISE), for processing and analyzing ad-hoc legacy scientific workflows.
To automatically generate the structural skeleton of these workflows, facilitating better understanding and maintenance.
To address the challenge of maintaining scientific workflows developed in scripting languages without prior formalization.

Main Methods:

The Workflow Instrumentation for Structure Extraction (WISE) method was developed to process legacy Python workflows.
WISE automatically extracts the structural skeleton of workflows, including identifying and analyzing calls to external tools.
The method does not require input workflows to be preprocessed into a specific workflow formalism.

Main Results:

WISE successfully processed several ad-hoc legacy scientific workflows written in Python.
The method automatically generated the structural skeleton for these diverse workflows.
Analysis of external tool calls was effectively integrated into the structural extraction process.

Conclusions:

The Workflow Instrumentation for Structure Extraction (WISE) method provides an effective solution for understanding and maintaining legacy scientific workflows.
WISE offers a flexible approach by not requiring pre-defined workflow formalisms, making it applicable to a wider range of existing scientific scripts.
This automated approach aids in managing complex computational pipelines in cross-disciplinary research environments.