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  1. slideshare.net

    Big Linked Data Federation - ExtremeEarth Open Workshop - Download as a PDF or view online for free. ... 27 Conclusions • We have developed a new version of Semagrow, Now, Semagrow is the first federation engine to be able to federate multiple big linked geospatial data sources. • We have developed a new version of the KOBE benchmarking ...
  2. earthanalytics.eu

    Querying, Federation and Extreme Analytics for Big Linked Geospatial Data Objectives The objective of this WP is to develop a set of tools for querying, integration and extreme analytics for the big information and knowledge that will be mined from Copernicus data and other auxiliary data sources using the techniques of WP2.
  3. earthanalytics.eu

    Federating big linked geospatial data sources with Semagrow Introduction. Semagrow [1] is an open source federated SPARQL query processor that allows combining, cross-indexing and, in general, making the best out of all public data, regardless of their size, update rate, and schema. Semagrow offers a single SPARQL endpoint that serves data from ...
  4. earthanalytics.eu

    The ExtremeEarth project develops Artificial Intelligence and Big Data technologies that scale to the petabytes of big Copernicus data, information and knowledge, and applies these technologies in two of the thematic exploitation platforms of the European Space Agency: the one dedicated to Food Security and the one dedicated to the Polar regions.
  5. slideshare.net

    3. 3 ExtremeEarth Main Objective • The main objective of ExtremeEarth is to go beyond the state-of-the-art and develop Artificial Intelligence and Big Data techniques and technologies that scale to the PBs of big Copernicus data, information and knowledge, and apply these technologies in two of the ESA TEPs: Food Security and Polar. • The technologies to be developed will extend the ...
  6. slideshare.net

    4. 4 Big Linked Geospatial Data Information and knowledge extracted from EO data is voluminous: 1 PB of Sentinel data may contain >750*103 products which will result in >450TB of information and knowledge (e.g., classes of objects). >106 PB of data in the Copernicus Open Access Hub ExtremeEarth will develop tools for transforming, integrating, querying and performing geospatial analytics for ...
  7. ris.utwente.nl

    of the ExtremeEarth software architecture. We summarize our main contributions as follows. 1) 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. 2) For the Polar use case, we present deep ...
  8. cordis.europa.eu

    The work carried out in ExtremeEarth so far pushes the state of the art in Artificial Intelligence for Earth Observation data. The specific innovative contributions of the project are the following: 1. The Hopsworks data and AI platform of LogicalClocks has been extended with new functionality that make it the platform of choice for developing big data and deep learning algorithms for Earth ...
  9. ieeexplore.ieee.org

    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 ...
  10. earthanalytics.eu

    ExtremeEarth is based on state-of-the-art technologies from the research areas of Remote Sensing, Deep Learning, Big Data, Distributed Systems, Semantic Web and Linked Geospatial Data.Existing implementations of these technologies by project partners will be re-engineered so that they scale to the big data, information, knowledge and extreme earth analytics of the Copernicus setting.

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