Empowering the use of Copernicus data in Latin America, the Caribbean and Europe
The BELLA Hackathon: Copernicus Innovation Development will be the first bicontinental innovation activity that seeks to enhance and make visible the work of research and development groups from universities, organizations and companies in Latin America, the Caribbean and Europe and to provide innovative and creative solutions to the challenges posed in the two winning concept notes of the Ideathon:
- Satellite Data Interpreter – SADAI (SAD – Decision Support System + AI – Artificial Intelligence)
- Platform for visualizing and interpreting climate data to support family farming in Latin American countries
Methodology
The registered groups will select one of the challenges proposed for this hackathon and will work on the innovative development of this challenge, the final result per group will be a final product that will evidence the development of the challenge and the possible implementation.
The evaluation of the final products will be in charge of expert judges in the topics worked on who will select the best 3 developments at the end of the challenge.
The hackathon will take place during 1 month from July 4th to July 31st, it will be virtual and will have synchronous and asynchronous sessions that will allow us to develop an agenda with training and mentoring spaces for the participants and spaces for the construction of the final products, as well as a simultaneous activity at the time of the opening and closing. The languages for the hackathon will be English and Spanish.
Background
During March 21st and 22nd, 2023, RedCLARA with the support of GÉANT, carried out the first Ideathon as a Copernicus innovation challenge between Latin America, the Caribbean and Europe.
The result we sought with the Ideathon was to pose a creative and innovative response to the following general problems:
- Processing: the large amount of data produced by the Copernicus Program requires specific strategies for processing the data. What kind of processing strategies, computational infrastructure and/or computational paradigm can be used to make that processing more efficient and faster.
- Artificial Intelligence (AI): How and with what techniques can AI reduce processing times and help find patterns that are useful for effective decision-making.
- Data access: What type of data architecture or cloud can contribute to faster and more efficient data access.
- Distribution: How to efficiently get information to decision-makers who need it.