| 1. |
- Hagos, Desta Haileselassie, et al.
(författare)
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ExtremeEarth Meets Satellite Data From Space
- 2021
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Ingår i: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1939-1404 .- 2151-1535. ; 14, s. 9038-9063
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Tidskriftsartikel (refereegranskat)abstract
- Bringing together a number of cutting-edge technologies that range from storing extremely large volumes of data all the way to developing scalable machine learning and deep learning algorithms in a distributed manner and having them operate over the same infrastructure poses unprecedented challenges. One of these challenges is the integration of European Space Agency (ESA)'s Thematic Exploitation Platforms (TEPs) and data information access service platforms with a data platform, namely Hopsworks, which enables scalable data processing, machine learning, and deep learning on Copernicus data, and development of very large training datasets for deep learning architectures targeting the classification of Sentinel images. In this article, we present the software architecture of ExtremeEarth that aims at the development of scalable deep learning and geospatial analytics techniques for processing and analyzing petabytes of Copernicus data. The ExtremeEarth software infrastructure seamlessly integrates existing and novel software platforms and tools for storing, accessing, processing, analyzing, and visualizing large amounts of Copernicus data. New techniques in the areas of remote sensing and artificial intelligence with an emphasis on deep learning are developed. These techniques and corresponding software presented in this article are to be integrated with and used in two ESA TEPs, namely Polar and Food Security TEPs. Furthermore, we present the integration of Hopsworks with the Polar and Food Security use cases and the flow of events for the products offered through the TEPs.
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| 2. |
- Koubarakis, Manolis, et al.
(författare)
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A retrospective on Telos as a metamodeling language for requirements engineering
- 2021
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Ingår i: Requirements Engineering. - : Springer. - 0947-3602 .- 1432-010X. ; 26, s. 1-23
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Tidskriftsartikel (refereegranskat)abstract
- Telos is a conceptual modeling language intended to capture software knowledge, such as software system requirements, domain knowledge, architectures, design decisions and more. To accomplish this, Telos was designed to be extensible in the sense that the concepts used to capture software knowledge can be defined in the language itself, instead of being built-in. This extensibility is accomplished through powerful metamodeling features, which proved very useful for interrelating heterogeneous models from requirements, model-driven software engineering, data integration, ontology engineering, cultural informatics and education. We trace the evolution of ideas and research results in the Telos project from its origins in the late eighties. Our account looks at the semantics of Telos, its various implementations and its applications. We also recount related research by other groups and the cross-influences of ideas thereof. We conclude with lessons learnt.
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