As part of the African Union Commission (AUC)’s Agenda 2063 which prioritizes skills revolution, with emphasis on soft skills for targeted knowledge-based economies in Africa in order to raise a critical mass of scientists in hardware, software and services, it partnered with the African Regional Centre for Space Science and Technology in French (CRASTE-LF), European Space Agency (ESA), Joint Research Centre (JRC) and EUMETSAT to train and equip African institutions on the integration of Cloud Computing to produce end-user-oriented Earth Observation (EO) services that are accurate and scalable. 

The 5-day training workshop took place from the 11th -15th November, 2019 at the facilities of CRASTE-LF and Faculty of Sciences of Mohammed V University of Rabat in Morocco, and drew over fifteen (15) nominees from GMES and Africa consortia and other African institutions that provide space services for communities, with focus on Earth observation.

The Training Objectives were to:

  1. learn about the diversified existing EO & Cloud Computing ecology by appreciating the pros and cons of each technological solution and be able to assess them with respect to the application needs, and
  2. get acquainted, through hands-on exercises, with a range of technological cloud computing solutions and digital analytical tools in different application context.

The course demonstrated the identification of datasets from big data as well as how cloud computing can enrich and scale EO service to national or even continental level. It included an the understanding of the diversified EO & Cloud Computing environment, and the criteria to apply when it comes to selecting a specific solution, that will satisfy the needs of a defined application sector in Africa. The programme also included hands-on exercises in a range of existing Cloud computing platforms, including the selection, computation and processing of EO big data.

As expected, the training impacted tacit knowledge and skills in the value-added-data chain starting from data identification to data utilization. At the end of the training, participants were equipped and capable of selecting the appropriate Cloud Computing environment for their application, and through it obtain datasets and process them in the cloud. It is believed that in no distant future, the training will inspire different institutions to apply cloud computing and digital analytical tools for deploying continuous services that answer the needs of users at scale.

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