Satellite

Biography

Biography: Dorian Gorgan

Abstract

The earth observation data repositories increasing dramatically by several terabytes each day become a big issue for organizations. The administration of the storage capacity of big datasets, access policy, data governance, protection, searching, fetching, and complex processing require high costs that force the organization to search for solutions to balance the cost and value of data. Data can create value only when it is used, and the data protection has to be oriented toward allowing innovation that sometimes depends on creative people, which achieve unexpected valuable results through a flexible and adaptive manner. The users need to describe and experiment themselves different complex algorithms through analytics in order to valorize data. The analytics uses descriptive and predictive models to gain valuable knowledge and information from data analysis. Possible solutions for advanced processing of big earth observation data are given by the HPC platforms such as cloud and cluster. With platforms becoming more complex and heterogeneous, the developing of applications is even harder and the efficient mapping of these applications to a suitable and optimum platform, working on huge distributed data repositories, is challenging and complex as well, even by using specialized software services. From the user point of view, an optimum environment gives acceptable execution times, offers a high level of usability by hiding the complexity of computing infrastructure, and supports an open accessibility and control to application entities and functionality. This presentation exemplifies some earth observation use cases based on flexible description of processing, and adaptive and portable execution over HPC infrastructures.