2023-06-29, 15:00–15:30 (Europe/Tirane), UBT D / N113 - Second Floor
The Massive Open Online Course - Earth Observation Open Data Science (MOOC EOODS) teaches the concepts of data cubes, cloud platforms, and open science in the context of Earth Observation (EO).
It aims at Earth Science students, researchers, and Data Scientists who want to increase their technical capabilities onto the newest standards in EO cloud computing. The course is designed as a MOOC that explains the concepts of cloud native EO and open science by applying them to a typical EO workflow from data discovery, data processing up to sharing the results in an open and FAIR way.
The EO College platform hosts the course and hands-on exercises are carried out directly on European EO cloud platforms, such as Euro Data Cube or openEO Platform, using open science tools like the Open Science Data Catalogue and STAC to embed the relevance of the learned concepts into real-world applications. The MOOC is an open learning experience relying on a mixture of animated lecture content and hands-on exercises created together with community renowned experts.
After finishing the course, the participants will understand the concepts of cloud native EO, be capable of independently using cloud platforms to approach EO related research questions and be confident in how to share research by adhering to the concepts of open science.
The MOOC is valuable for the EO community and open science as there is currently no learning resource available where the concepts of cloud native computing and open science in EO are taught jointly to bridge the gap towards the recent cloud native advancements in EO. The course is open to everybody, thus serving as teaching material for a wide range of purposes including universities and industry, maximizing the outreach to potential participants.
Our talk will give an overview of the MOOC at the current status. Furthermore, we encourage review, feedback on its content and discussion.
I'm a geographer with a focus on geoinformatics, remote sensing and their application to environmental applications - which should be barrierfree and open source.
I'm providing, optimizing and automizing remote sensing and gis workflows and tools, setting up scalable computing environments, working on big earth observation data cloud infrastructures and helping to bring research results into an easily accessible and digestible format.