European Big Data Value Forum Agenda by Whova

Dimitris Bilidas

Research Associate, National and Kapodistrian University of Athens

Dimitris Bilidas is a researcher at the Management of Data, Information and Knowledge group, in the Dept. of Informatics and Telecommunications, National and Kapodistrian University of Athens. He obtained a B.Sc. from Department of Informatics, University of Piraeus and a M.Sc. in Advanced Information Systems from Department of Informatics and Telecommunications in National and Kapodistrian University of Athens, where he is currently a PhD candidate under the supervision of Professor Manolis Koubarakis, in the area of query languages for the Semantic Web and Distributed Query Processing. Mr. Bilidas has extensive research experience in several Greek and European research projects (ExtremeEarth, Optique, Copernicus App Lab, Indigo, Xenios). In the context of the ExtremeEarth project he is developing solutions for distributed geospatial analytics over large semantic web graph databases.

Dimitris is speaking at

Parallel session on Big Data and Artificial Intelligence Techniques for Earth Observation (ExtremeEarth project sponsored session)

Application Track 5 - Smart society

November 3, 2020

2:00 pm - 3:00 pm

Speakers

Manolis Koubarakis (Parallel session chair) ExtremeEarth
Claudia Paris (Speaker) Assistant Professor, University of Trento
Dimitris Bilidas (Speaker) Research Associate, National and Kapodistrian University of Athens
Theofilos Kakantousis (Speaker) VP of Product, Logical Clocks
Habib Ullah (Speaker) Postdoctoral Fellow, The Arctic University of Norway

Description

The objective of this session to present the Big Data and AI Techniques for Earth Observation pioneered by the H2020 project “ExtremeEarth: From Copernicus Big Data to Extreme Earth Analytics” (http://earthanalytics.eu/).

ExtremeEarth concentrates on Copernicus data, probably the most paradigmatic case of big open data in the European Union today, and arguably one of the most valuable for our planet . The extraction of knowledge and commercial value from Copernicus data is also of utmost importance for the European industry and society. ExtremeEarth addresses this issue explicitly through its two use cases that bring together the Food Security and Polar TEPs. Knowledge extraction is done through deep learning techniques that work at the extreme scale of data expected in Copernicus. ExtremeEarth also addresses the management of the information and knowledge extracted from Copernicus data using Semantic Web and Linked Data technologies. The implementation of these technologies in the European Hops data platform will enable the computation of extreme geospatial analytics on top of Copernicus information and knowledge.