The Blue-Cloud Hackathon (7-9 February 2022) invited marine scientists & researchers, data scientists, ICT experts, innovators, students, and anyone passionate about the Ocean to explore and test Blue-Cloud: the new, Open Science platform for the marine domain offering a wealth of data, analytical tools and computing power to support you in developing solutions for a safe, healthy, productive, predictive and transparent Ocean.
Participants were challenged to develop applications that contribute to improving knowledge of marine ecosystems; support the transition to a greener, blue economy; advance Ocean literacy; and/or enhance international collaboration towards achieving the Sustainable Development Goals (SDGs) of the United Nations Agenda 2030. Teams were grouped into categories and faced different hackathon challenges.
Find here the teams that participated in the challenge and discover the people behind, the ideas, topics and video pitches realised.
More information about the outcomes of the hackathon can be found here.
WILDCARD - Hack the Blue-Cloud! - Challenge 4
UNDERSTANDING THE OCEAN - Challenge: 1A
PREDICTING ENVIRONMENTAL RISKS - Challenge: 3A
Our team consists of open-minded freelancers who are committed to building a blue-environment related project that serves cutting edge artificial intelligence and machine learning technologies.
This team, founded by two deep learning developers from Hungary, invented DataDolphin for this hackathon. Outsiders from the scope of marine biology, are familiar with data science
<PREDICTING ENVIRONMENTAL RISKS - Challenge: 3A>
<FEEDING THE WORLD - Challenge: 2A>
AtlantECO hacc-UP - ETH Environmental Physics guinea-pigs testing the Blue Cloud infrastructure and its potential links with the HORIZON AtlantECO project
<UNDERSTANDING THE OCEAN - Challenge: 1A>
What is the tool? A dynamic real-time based 3d virtual marine ecosystem made by NFT.
Why this tool? The ecosystem is dynamic and having real-time data is necessary for understanding the current situation of the ecosystem.
<PREDICTING ENVIRONMENTAL RISKS - Challenge: 3B>