Using provenance to manage knowledge of in silico experiments

Area of Science:

• Bioinformatics
• Computational Biology
• eScience

Background:

• Bioinformatics is increasingly adopting an industrial setting within eScience.
• Computational experiments in bioinformatics require scientific rigor comparable to laboratory science.
• Knowledge management is essential for maintaining the integrity of in silico research.

Purpose of the Study:

• To address knowledge management challenges in in silico bioinformatics experimentation.
• To highlight the importance of recording experimental provenance in computational studies.
• To review existing systems supporting provenance generation and collection.

Main Methods:

• The article reviews knowledge management issues related to in silico experimentation.
• It emphasizes the necessity of documenting experimental provenance (what, where, how, why).
• The review considers the context of eScience and the industrialization of bioinformatics.

Main Results:

• Provenance recording is a critical aspect of scientific best practice for in silico experiments.
• Effective provenance management is necessary for introducing scientific rigor into routine bioinformatics.
• Existing systems offer support for generating and collecting provenance information.

Conclusions:

• In silico experimental protocols serve as a form of knowledge management for bioinformatics analyses.
• Robust provenance tracking is vital for the reproducibility and reliability of computational experiments.
• Addressing provenance is key to advancing scientific rigor in bioinformatics research.