research-article

From Copernicus Big Data to Big Information and Big Knowledge: A Demo from the Copernicus App Lab Project

Authors:

Konstantina Bereta,

Hervé Caumont,

Manolis Koubarakis,

Despina-Athanasia Pantazi,

George Stamoulis,

Valentijn Venus,

Firman WahyudiAuthors Info & Claims

CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge Management

Pages 1911 - 1914

https://doi.org/10.1145/3269206.3269232

Published: 17 October 2018 Publication History

Abstract

Copernicus is the European program for monitoring the Earth. It consists of a set of complex systems that collect data from satellites and in-situ sensors, process this data and provide users with reliable and up-to-date information on a range of environmental and security issues. The data collected by Copernicus is made available freely following an open access policy. Information extracted from Copernicus data is disseminated to users through the Copernicus services which address six thematic areas: land, marine, atmosphere, climate, emergency and security. We present a demo from the Horizon 2020 Copernicus App Lab project which takes big data from the Copernicus land service, makes it available on the Web as linked geospatial data and interlinks it with other useful public data to aid the development of applications by developers that might not be Earth Observation experts. Our demo targets a scenario where we want to study the "greenness" of Paris.

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Cited By

Wu JOrlandi FO'Sullivan DDev S(2024)On the Use of Virtual Knowledge Graphs to Improve Environmental Sensor Data AccessibilityIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing10.1109/JSTARS.2024.337038917(6671-6682)Online publication date: 2024
(2023)Geospatial Data ScienceundefinedOnline publication date: 9-Jun-2023
Foufoulas YSimitsis AStamatogiannakis LIoannidis Y(2022)YeSQLProceedings of the VLDB Endowment10.14778/3547305.354732815:10(2270-2283)Online publication date: Jun-2022
Show More Cited By

Index Terms

From Copernicus Big Data to Big Information and Big Knowledge: A Demo from the Copernicus App Lab Project
1. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Data exchange

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cover image ACM Conferences

CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge Management

October 2018

2362 pages

ISBN:9781450360142

DOI:10.1145/3269206

General Chair:
Alfredo Cuzzocrea
University of Trieste, Italy
,
Program Chairs:
James Allan
University of Massachusetts, USA
,
Norman Paton
University of Manchester, United Kingdom
,
Divesh Srivastava
AT&T Labs Research, USA
,
Rakesh Agrawal
Data Insights Lab, USA
,
Andrei Broder
Google Research, USA
,
Mohammed Zaki
Rensselaer Polytechnic Institute, USA
,
Selcuk Candan
Arizona State University, USA
,
Alexandros Labrinidis
University of Pittsburgh, USA
,
Assaf Schuster
Technion, Israel
,
Haixun Wang
Google Research, USA

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 17 October 2018

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EU H2020 project Copernicus App Lab

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CIKM '18

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CIKM '18: The 27th ACM International Conference on Information and Knowledge Management

October 22 - 26, 2018

Torino, Italy

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CIKM '18 Paper Acceptance Rate 147 of 826 submissions, 18%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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CIKM '25

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The 34th ACM International Conference on Information and Knowledge Management

November 10 - 14, 2025

Seoul , Republic of Korea

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Cited By

Wu JOrlandi FO'Sullivan DDev S(2024)On the Use of Virtual Knowledge Graphs to Improve Environmental Sensor Data AccessibilityIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing10.1109/JSTARS.2024.337038917(6671-6682)Online publication date: 2024
(2023)Geospatial Data ScienceundefinedOnline publication date: 9-Jun-2023
Foufoulas YSimitsis AStamatogiannakis LIoannidis Y(2022)YeSQLProceedings of the VLDB Endowment10.14778/3547305.354732815:10(2270-2283)Online publication date: Jun-2022
Bereta KCaumont HGoor EKoubarakis MPantazi DStamoulis GUbels SVenus VWahyudi FCuzzocrea AAllan JPaton NSrivastava DAgrawal RBroder AZaki MCandan SLabrinidis ASchuster AWang H(2018)From Copernicus Big Data to Big Information and Big KnowledgeProceedings of the 27th ACM International Conference on Information and Knowledge Management10.1145/3269206.3269232(1911-1914)Online publication date: 17-Oct-2018

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