Biodiversity data: From data collection to publication

This is an example of the course programme, which may be subject to slight changes from year to year.

The first four days will consist of lectures followed by exercises. Sub-group projects will be carried out on the last day.

Introduction and overview

• What is data/metadata?
• Major types of biodiversity data
• The data ecosystem in France and in academia
• The data cycle
• Achieving a high degree of “FAIRification”
• Current challenges (in academia and beyond)

Data acquisition

• Best practices for data collection (field, laboratory, etc.)
• Access to existing data (APIs, web scraping, text mining, etc.)
• Raw data vs. derived data

Data management

• Structuring (SQL, CSV files, etc.)
• Processing, cleaning and standardizing

Legal aspects

• Sharing, licensing, etc.

Opening data

• Data management plan
• (Meta)data: standards
• Storage and archiving
• Dissemination and sharing
• Enhanced value: the data paper