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research-article

Sextant

Authors:

Charalampos Nikolaou,

Kallirroi Dogani,

Konstantina Bereta,

Manos Karpathiotakis,

Kostis Kyzirakos,

Manolis KoubarakisAuthors Info & Claims

Web Semantics: Science, Services and Agents on the World Wide Web, Volume 35, Issue P1

Pages 35 - 52

https://doi.org/10.1016/j.websem.2015.09.004

Published: 01 December 2015 Publication History

Abstract

The linked open data cloud is constantly evolving as datasets get continuously updated with newer versions. As a result, representing, querying, and visualizing the temporal dimension of linked data is crucial. This is especially important for geospatial datasets that form the backbone of large scale open data publication efforts in many sectors of the economy (e.g., the public sector, the Earth Observation sector). Although there has been some work on the representation and querying of linked geospatial data that change over time, to the best of our knowledge, there is currently no tool that offers spatio-temporal visualization of such data. This is in contrast with the existence of many tools for the visualization of the temporal evolution of geospatial data in the GIS area. In this article, we present Sextant, a Web-based system for the visualization and exploration of time-evolving linked geospatial data and the creation, sharing, and collaborative editing of "temporally-enriched" thematic maps which are produced by combining different sources of such data. We present the architecture of Sextant, give examples of its use and present applications in which we have deployed it.

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Cited By

Troumpoukis AKlampanos IPantazi DAlbughdadi MBaousis VBarrilero OBojor ABranco PBruzzone LChietera AFournand PHall RLazzarini MLuna ANousias APerentis CPetrakis GPunjani DRöbl DStamoulis GTsalapati EUrbanavičiūtė IWeikmann GZiouvelou XZiółkowski MKoubarakis MKarkaletsis V(2024)European AI and EO convergence via a novel community-driven framework for data-intensive innovationFuture Generation Computer Systems10.1016/j.future.2024.06.013160:C(505-521)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1016/j.future.2024.06.013
Milon-Flores DBernard CGensel JGiuliani GChatenoux BDao H(2024)Publication of Satellite Earth Observations in the Linked Open Data Cloud: Experiment Through the TRACES ProjectWeb and Wireless Geographical Information Systems10.1007/978-3-031-60796-7_5(67-85)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1007/978-3-031-60796-7_5
Bilidas DMantas AYfantis FStamoulis GKoubarakis MKondylatos SPrapas IPapoutsis IRenz MNascimento M(2023)Fire Risk Management using Data Cubes, Machine Learning and OBDA systemsProceedings of the 31st ACM International Conference on Advances in Geographic Information Systems10.1145/3589132.3625615(1-4)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3589132.3625615
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Sextant
1. Applied computing
  1. Physical sciences and engineering
2. Information systems
  1. Information systems applications

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Reviews

Reviewer: Salvatore F. Pileggi

Large data sets of linked geospatial data are progressively appearing on the web. It is a direct consequence of the intense research activity of recent years, which has consolidated concepts, models, and related technology. These data sets are increasing in number as well as in size, defining a trend that requires novel approaches and cutting-edge applications. Geospatial information rarely reflects a static reality, as most of the time it represents contexts and phenomena in their evolution. Therefore, the temporal dimension of data can play a crucial role in the context of many applications. This paper deals with the spatiotemporal analysis of linked data. Sextant, the tool described in the paper, allows the browsing and the visualization of time-evolving linked geospatial data in a context of interoperability and flexibility. The paper is interesting in all its parts. As a reader, I appreciate that the key concepts are introduced and clearly explained before going through technical details. Furthermore, the characteristics of the tool are clearly stated and future directions seem convincing. This is definitely an interesting contribution to the field. Online Computing Reviews Service

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cover image Web Semantics: Science, Services and Agents on the World Wide Web

Web Semantics: Science, Services and Agents on the World Wide Web Volume 35, Issue P1

December 2015

63 pages

ISSN:1570-8268

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Copyright © Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 December 2015

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Troumpoukis AKlampanos IPantazi DAlbughdadi MBaousis VBarrilero OBojor ABranco PBruzzone LChietera AFournand PHall RLazzarini MLuna ANousias APerentis CPetrakis GPunjani DRöbl DStamoulis GTsalapati EUrbanavičiūtė IWeikmann GZiouvelou XZiółkowski MKoubarakis MKarkaletsis V(2024)European AI and EO convergence via a novel community-driven framework for data-intensive innovationFuture Generation Computer Systems10.1016/j.future.2024.06.013160:C(505-521)Online publication date: 1-Nov-2024
Milon-Flores DBernard CGensel JGiuliani GChatenoux BDao H(2024)Publication of Satellite Earth Observations in the Linked Open Data Cloud: Experiment Through the TRACES ProjectWeb and Wireless Geographical Information Systems10.1007/978-3-031-60796-7_5(67-85)Online publication date: 18-Jun-2024
Bilidas DMantas AYfantis FStamoulis GKoubarakis MKondylatos SPrapas IPapoutsis IRenz MNascimento M(2023)Fire Risk Management using Data Cubes, Machine Learning and OBDA systemsProceedings of the 31st ACM International Conference on Advances in Geographic Information Systems10.1145/3589132.3625615(1-4)Online publication date: 13-Nov-2023
(2023)Geospatial Data ScienceundefinedOnline publication date: 9-Jun-2023
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Soylu AKharlamov EZheleznyakov DJimenez-Ruiz EGiese MSkjæveland MHovland DSchlatte RBrandt SLie HHorrocks I(2018)OptiqueVQSSemantic Web10.3233/SW-1802939:5(627-660)Online publication date: 1-Jan-2018
Voutos YMylonas PJohn KGrammati PStefanos GChristos D(2018)A semantic data model for sensory spatio-temporal environmental conceptsProceedings of the 22nd Pan-Hellenic Conference on Informatics10.1145/3291533.3291571(180-185)Online publication date: 29-Nov-2018
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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