Create user-friendly and interactive data visualisation tools that enable researchers and policymakers to explore and understand biodiversity data cubes effectively.
Explore methods to integrate diverse datasets, such as satellite imagery and climate data with biodiversity data cubes that can provide a comprehensive view of ecosystems and species distributions.
Develop algorithms and techniques to assess biodiversity trends from data cubes, identify critical areas for conservation, and monitor changes in species distributions over time and space.
Build models that predict species habitat suitability, biodiversity hotspots, and potential threats to specific ecosystems.
Disseminate standards and methods for ensuring data cube interoperability, making it easier to share and combine biodiversity data cubes with other environmental data from a variety of different sources.
Develop techniques to identify and handle data inconsistencies and errors in biodiversity data cubes, ensuring the accuracy and reliability of the analyses.
Examine ways upon which data services can be built to access and interact with biodiversity data cubes.
Design educational tools and platforms using biodiversity data cubes to raise awareness about the importance of biodiversity conservation and engage the public in conservation efforts.
Identify and explore potential use cases for biodiversity data cubes across various sectors, such as agriculture, health, urban planning, and conservation policy-making.
Organise tutorials that provide participants with the necessary skills and knowledge to work with data cubes once they return home. These will cover topics such as building cubes, data analysis and visualisation.