November 2024 I Course I Cesab I Other subjects
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[FRB-CESAB] Biodiversity data: From data collection to publication – 2024
This five-day training course aims to work on the different stages of the data cycle, from acquisition to opening, including management, storage and the drafting of data papers.
Pre-registrations are now open!
To pre-register, fill out the form at the bottom of the page. Registrations will be confirmed after selection of candidates at the end of June.
The CESAB (Centre for Biodiversity Synthesis and Analysis), the French Biodiversity Data Hub (PNDB, Pôle National de Données de Biodiversité), and GBIF France (Global Biodiversity Information Facility for France) organize the first edition of the training course “Biodiversity data: From data collection to publication”. This five-day course aims to 1) contextualize the issues surrounding the understanding, sharing and (re)use of biodiversity data and metadata, and 2) enhance the skills of communities involved in one or more stages of the data cycle.
This training will be given in French and will take place from November 4th to 8th 2024, at CESAB in Montpellier. The fees cost 150 € for the whole week – lunches included. Commuting, accommodation and evening meals shall be borne by participants.
Find the training course on GitHub
A good mastering of the R software is required
List of organisers:
- Nicolas CASAJUS (FRB-CESAB)
- Camille COUX (FRB-CESAB)
- Yvan LE BRAS (PNDB)
- Olivier NORVEZ (PNDB)
- Anne-Sophie ARCHAMBEAU (GBIF France)
- Sophie PAMERLON (GBIF France)
INFORMATIONS PRATIQUES
Formation:
4 to 8 November 2024
- Pre-registration opening:
6 May 2024
- Pre-registration deadline:
2 June 2024, midnight (CEST)
- Inscription confirmation:
Late June 2024
CESAB – FRB
5, rue de l’École de médecine
34000 Montpellier
Pre-program
The first four days will consist of lectures followed by exercises:
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)
- Best practices for data collection (field, laboratory, etc.)
- Access to existing data (APIs, web scraping, text mining, etc.)
- Raw data vs. derived data
- Structuring (SQL, CSV files, etc.)
- Processing, cleaning and standardizing
- Sharing, licensing, etc.
- Data management plan
- (Meta)data: standards
- Storage and archiving
- Dissemination and sharing
- Enhanced value: the data paper
Sub-group projects will be carried out on the last day.
Pre-registration form
Merci de répondre en français.
CO-ORGANISATEUR
