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Identifying the key resources and missing elements to build a knowledge graph dedicated to spatial dataset search / Mehdi Zrhal in Procedia Computer Science, vol 207 (2022)  

Public [article]  inProcedia Computer Science > vol 207 (2022) . - pp 2911 - 2920 Titre : Identifying the key resources and missing elements to build a knowledge graph dedicated to spatial dataset search Type de document : Article/Communication Auteurs : Mehdi Zrhal , Auteur ; Bénédicte Bucher , Auteur ; Fayçal Hamdi , Auteur ; Marie-Dominique Van Damme , Auteur Année de publication : 2022 Conférence : KES 2022, 26th International Conference Knowledge-Based and Intelligent Information & Engineering Systems 07/09/2022 09/09/2022 Vérone Italie OA proceedings Article en page(s) : pp 2911 - 2920 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] jeu de données localisées [Termes IGN] recherche d'information géographique [Termes IGN] réseau sémantique Résumé : (auteur) The number of spatial datasets available online has increased exponentially in recent years. Therefore, the search for spatial datasets is becoming a fourishing research field. The use of knowledge graphs has become rampant in search engines and in information retrieval. In this article, we identify the main resources needed and those missing to allow a knowledge graph to support spatial dataset search. We then apply our approach to the water domain in France by building a dedicated knowledge graph and describe an evaluation method to measure its effectiveness. Numéro de notice : A2022-695 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.procs.2022.09.349 Date de publication en ligne : 19/10/2022 En ligne : https://doi.org/10.1016/j.procs.2022.09.349 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101910 [article]

GIS-KG: building a large-scale hierarchical knowledge graph for geographic information science / Jiaxin Du in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 5 (May 2022) . - pp 873 - 897 Titre : GIS-KG: building a large-scale hierarchical knowledge graph for geographic information science Type de document : Article/Communication Auteurs : Jiaxin Du, Auteur ; Shaohua Wang, Auteur ; Xinyue Ye, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 873 - 897 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] apprentissage profond [Termes IGN] approche hiérarchique [Termes IGN] exploration de données [Termes IGN] ingénierie des connaissances [Termes IGN] ontologie [Termes IGN] recherche d'information géographique [Termes IGN] réseau sémantique [Termes IGN] traitement du langage naturel Résumé : (auteur) An organized knowledge base can facilitate the exploration of existing knowledge and the detection of emerging topics in a domain. Knowledge about and around Geographic Information Science and its associated system technologies (GIS) is complex, extensive and emerging rapidly. Taking the challenge, we built a GIS knowledge graph (GIS-KG) by (1) merging existing GIS bodies of knowledge to create a hierarchical ontology and then (2) applying deep-learning methods to map GIS publications to the ontology. We conducted several experiments on information retrieval to evaluate the novelty and effectiveness of the GIS-KG. Results showed the robust support of GIS-KG for knowledge search of existing GIS topics and potential to explore emerging research themes. Numéro de notice : A2022-341 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2005795 Date de publication en ligne : 26/11/2021 En ligne : https://doi.org/10.1080/13658816.2021.2005795 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100515 [article]

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Enriching the metadata of map images: a deep learning approach with GIS-based data augmentation / Yingjie Hu in International journal of geographical information science IJGIS, vol 36 n° 4 (April 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 4 (April 2022) . - pp 799 - 821 Titre : Enriching the metadata of map images: a deep learning approach with GIS-based data augmentation Type de document : Article/Communication Auteurs : Yingjie Hu, Auteur ; Zhipeng Gui, Auteur ; Jimin Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 799 - 821 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] descripteur [Termes IGN] données d'entrainement sans étiquette [Termes IGN] image cartographique [Termes IGN] métadonnées [Termes IGN] projection [Termes IGN] système d'information géographique [Termes IGN] Web Map Service [Termes IGN] web mapping Résumé : (auteur) Maps in the form of digital images are widely available in geoportals, Web pages, and other data sources. The metadata of map images, such as spatial extents and place names, are critical for their indexing and searching. However, many map images have either mismatched metadata or no metadata at all. Recent developments in deep learning offer new possibilities for enriching the metadata of map images via image-based information extraction. One major challenge of using deep learning models is that they often require large amounts of training data that have to be manually labeled. To address this challenge, this paper presents a deep learning approach with GIS-based data augmentation that can automatically generate labeled training map images from shapefiles using GIS operations. We utilize such an approach to enrich the metadata of map images by adding spatial extents and place names extracted from map images. We evaluate this GIS-based data augmentation approach by using it to train multiple deep learning models and testing them on two different datasets: a Web Map Service image dataset at the continental scale and an online map image dataset at the state scale. We then discuss the advantages and limitations of the proposed approach. Numéro de notice : A2022-258 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.1080/13658816.2021.1968407 En ligne : https://doi.org/10.1080/13658816.2021.1968407 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100231 [article]

Architecture for semantic web service composition in spatial data infrastructures / Deniztan Ulutaş Karakol in Survey review, vol 54 n° 382 (January 2022)  

Public [article]  inSurvey review > vol 54 n° 382 (January 2022) . - pp 1 - 16 Titre : Architecture for semantic web service composition in spatial data infrastructures Type de document : Article/Communication Auteurs : Deniztan Ulutaş Karakol, Auteur ; Cetin Cömert, Auteur Année de publication : 2022 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] accès aux données localisées [Termes IGN] conception orientée utilisateur [Termes IGN] langage naturel (informatique) [Termes IGN] ontologie [Termes IGN] OWL [Termes IGN] web sémantique Résumé : (auteur) The importance of geospatial data has rendered it to be used in decision-making in both public and private sectors. The purpose of this study was to employ Semantic Web Technology (SWT) for the problems of Web Service Composition (WSC) in the context of Spatial Data Infrastructures (SDI). Some of these problems are identifying the workflow sequence and the user goal, discovering services according to service parameters, and matching these parameters. As a suggestion for the solution of all these problems a semi-automated WSC architecture was proposed in this study. In terms of architecture, users state their ‘goal’ with a natural language sentence. By semantically matching this sentence with a Spatial Services Ontology (SSO), the corresponding ‘abstract’ WSC was ‘located’ and the ‘concrete’ WSC was formed. Although there are still problems waiting to be solved due to the scope of the work, this study makes a valuable contribution to the area. Numéro de notice : A2022-110 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1858255 Date de publication en ligne : 25/12/2020 En ligne : https://doi.org/10.1080/00396265.2020.1858255 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99627 [article]

Building a collaborative online catalogue of geoportals in Brazil / Eduardo Silverio da Silva in Boletim de Ciências Geodésicas, vol 27 n° 4 ([01/12/2021])  

Public [article]  inBoletim de Ciências Geodésicas > vol 27 n° 4 [01/12/2021] . - 16 p. Titre : Building a collaborative online catalogue of geoportals in Brazil Type de document : Article/Communication Auteurs : Eduardo Silverio da Silva, Auteur ; Silvana Philippi Camboim, Auteur Année de publication : 2021 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] Brésil [Termes IGN] catalogue de données localisées [Termes IGN] géoportail [Termes IGN] infrastructure nationale des données localisées [Termes IGN] recherche d'information géographique [Termes IGN] WebSIG Résumé : (auteur) It is currently possible to account for several institutions with geographic data shared through the INDE portal, with more than half of it being from federal jurisdiction. However, there are subnational geoportals not integrated with this infrastructure, which is difficult to quantify. Therefore, the research problem of this study is finding the state of subnational geographic viewers’ availability, with the general objective of producing a Brazilian panorama and to identify factors that facilitate this availability. A research methodology based on different sources was applied in 27 states and 999 municipalities. As a result, we identified 17 regional, 82 state, and 274 municipal geoportals, with the highest concentration in the South and Southeast regions and lowest in the Northern region. In order to find factors related to geoportals availability, twenty characteristics of each municipality were collected, and Pearson coefficients were calculated, revealing significant correlations for population, economic and tax factors, and non-significant correlations for location factors. This acquired information is essential for the community and must be kept up to date. For this, an online collaborative map based on free software was created, allowing access without registration for data visualization and the registration of users for sending updates to the map. Numéro de notice : A2021-960 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1590/s1982-21702021000400026 Date de publication en ligne : 17/12/2021 En ligne : https://doi.org/10.1590/s1982-21702021000400026 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100072 [article]

Fully automated pose estimation of historical images in the context of 4D geographic information systems utilizing machine learning methods / Ferdinand Maiwald in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)  

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Integration of heterogeneous terrain data into Discrete Global Grid Systems / Mingke Li in Cartography and Geographic Information Science, vol 48 n° 6 (October 2021)  

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A web GIS-based integration of 3D digital models with linked open data for cultural heritage exploration / Ikrom Nishanbaev in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)  

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Implementing a mass valuation application on interoperable land valuation data model designed as an extension of the national GDI / Arif Cagdas Aydinoglu in Survey review, Vol 53 n° 379 (July 2021)  

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Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data / Yunhao Zheng in Computers, Environment and Urban Systems, vol 85 (January 2021)  

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Model and reality: Connecting BIM and the built environment / Gustaf Uggla (2021)  

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Représentation sémantique de données géospatiales au service de l'analyse de changements / Jordan Dorne (2021)  

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Spatial dataset search: Building a dedicated knowledge graph / Mehdi Zrhal (2021)  

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Streets of London: Using Flickr and OpenStreetMap to build an interactive image of the city / Azam Raha Bahrehdar in Computers, Environment and Urban Systems, vol 84 (November 2020)  

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GNSS scale determination using calibrated receiver and Galileo satellite antenna patterns / Arturo Villiger in Journal of geodesy, vol 94 n° 9 (September 2020)  

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