BioVeL: a virtual laboratory for data analysis and modelling in biodiversity science and ecology

Area of Science:

• Biodiversity science and ecology
• Computational biology
• Environmental science

Background:

• Biodiversity forecasting and policy support rely on large electronic datasets and computational analysis.
• Distributed data resources and expertise pose challenges for modern scientists.
• Web services and scientific workflow systems offer solutions for in silico science but are underutilized in ecology.

Purpose of the Study:

• To develop and provide an accessible virtual laboratory for biodiversity science and ecology.
• To facilitate in silico data analysis, modeling, and prediction.
• To integrate existing tools and practices for ecological research.

Main Methods:

• Developed BioVeL, a freely accessible internet-based virtual laboratory.
• Integrated over 60 curated Web services for data access and analysis.
• Exposed R programs and created reusable scientific workflows.
• Provided on-line collaboration, experiment documentation, and computational support.

Main Results:

• BioVeL offers functions for data analysis, in silico modeling, and collaboration.
• Over 60 Web services were developed and improved for diverse analytical tasks.
• Reusable workflows were composed using Web services and R programs.
• The virtual laboratory was made publicly accessible and promoted for user engagement.

Conclusions:

• An operational, scalable, and flexible internet-based virtual laboratory has been delivered.
• The platform addresses new demands for data processing and analysis in biodiversity science.
• Existing tools from various disciplines are successfully integrated for ecological research.