Course Objective
The main objective of the course is to provide participants with knowledge and practical experience on the principles and methods for ensuring biodiversity data quality and cleaning.

Date and Venue
June 23–25, 2025, PORBIOTA Room (Room 48), Instituto Superior de Agronomia (Main Building), Lisbon.

Description
This theoretical and practical course will explore data quality principles and their application through data detection and cleaning practices, using hands-on examples.
Data quality is one of the most important factors determining the potential use of a dataset. This quality is shaped by multiple elements throughout the information production and processing chain — from initial recording or capture to final use and interpretation. Biodiversity data quality is also tied to several dimensions, including taxonomy, spatial data, metadata, storage, and publication.

The course will cover the following topics:

• Principles of data quality
• Tools and protocols for data quality
• OpenRefine
• Taxonomic and spatial data quality

Requirements
Previous experience in recording, maintaining, and managing biodiversity data is helpful for getting the most out of the course, but it is not required. Ideally, participants should bring a biodiversity dataset to use in the practical sessions on quality control, data detection, and cleaning. If bringing a dataset is not possible, a sample dataset will be provided.
Participants may bring their own laptop or use the computers available in the classroom.

Registration
Registration is open until July 9, 2025. Please use the registration form provided. In addition to your personal information, you should include your motivations for participating in the course and a short summary of your previous experience related to biodiversity data management.

The list of selected participants will be published on this page on July 11, 2025.

More information [here].