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Perspectives on automated composition of workflows in the life sciences
Anna-Lena Lamprecht1, Magnus Palmblad2, Jon Ison3
1Utrecht University, 3584 CS Utrecht, The Netherlands.
F1000Research
|November 22, 2021
Summary
Automating scientific workflow composition in life sciences is crucial for robust, reusable research. This workshop explored methods and a roadmap for developing standardized, automated workflows.
Area of Science:
- Life Sciences
- Computational Biology
- Bioinformatics
Background:
- Scientific data analysis relies on computational workflows, but manual composition is challenging.
- Lack of standards hinders annotation, assembly, and implementation of life science workflows.
Purpose of the Study:
- Summarize a workshop on automated workflow composition in life sciences.
- Survey past initiatives, current state, and future perspectives.
- Propose a roadmap for automated workflow development.
Main Methods:
- Reviewed previous automation initiatives.
- Discussed semantic domain modeling, automation technologies, and workflow assessment.
- Defined a six-stage scientific workflow life cycle.
Main Results:
- Identified semantic domain modeling as a bottleneck but noted progress in life sciences.
- Highlighted the potential of semantic technologies for workflow exploration and composition.
- Emphasized the need for benchmarking and large-scale deployment.
Conclusions:
- Automated workflow development can lead to more robust, reusable, and sustainable scientific workflows.
- Community and individual actions are needed to achieve automated workflow development.
- Advancements in semantic technologies and standardization are key.
