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Auteur Simon Scheider |
Documents disponibles écrits par cet auteur



Deeply integrating linked data with geographic information systems / Gengchen Mai in Transactions in GIS, vol 23 n° 3 (June 2019)
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Titre : Deeply integrating linked data with geographic information systems Type de document : Article/Communication Auteurs : Gengchen Mai, Auteur ; Krzysztof Janowicz, Auteur ; Bo Yan, Auteur ; Simon Scheider, Auteur Année de publication : 2019 Article en page(s) : pp 579 - 600 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes descripteurs IGN] connecteur logiciel
[Termes descripteurs IGN] graphe
[Termes descripteurs IGN] ontologie
[Termes descripteurs IGN] système d'information géographique
[Termes descripteurs IGN] Web des donnéesRésumé : (Auteur) The realization that knowledge often forms a densely interconnected graph has fueled the development of graph databases, Web‐scale knowledge graphs and query languages for them, novel visualization and query paradigms, as well as new machine learning methods tailored to graphs as data structures. One such example is the densely connected and global Linked Data cloud that contains billions of statements about numerous domains, including life science and geography. While Linked Data has found its way into everyday applications such as search engines and question answering systems, there is a growing disconnect between the classical ways in which Geographic Information Systems (GIS) are still used today and the open‐ended, exploratory approaches used to retrieve and consume data from knowledge graphs such as Linked Data. In this work, we conceptualize and prototypically implement a Linked Data connector framework as a set of toolboxes for Esri's ArcGIS to close this gap and enable the retrieval, integration, and analysis of Linked Data from within GIS. We discuss how to connect to Linked Data endpoints, how to use ontologies to probe data and derive appropriate GIS representations on the fly, how to make use of reasoning, how to derive data that are ready for spatial analysis out of RDF triples, and, most importantly, how to utilize the link structure of Linked Data to enable analysis. The proposed Linked Data connector framework can also be regarded as the first step toward a guided geographic question answering system over geographic knowledge graphs. Numéro de notice : A2019-255 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12538 date de publication en ligne : 11/06/2019 En ligne : https://doi.org/10.1111/tgis.12538 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93013
in Transactions in GIS > vol 23 n° 3 (June 2019) . - pp 579 - 600[article]Computing with cognitive spatial frames of reference in GIS / Simon Scheider in Transactions in GIS, vol 22 n° 5 (October 2018)
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Titre : Computing with cognitive spatial frames of reference in GIS Type de document : Article/Communication Auteurs : Simon Scheider, Auteur ; Jürgen Hahn, Auteur ; Paul Weiser, Auteur ; Werner Kuhn, Auteur Année de publication : 2018 Article en page(s) : pp 1083 - 1104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes descripteurs IGN] espace vectoriel
[Termes descripteurs IGN] logique floue
[Termes descripteurs IGN] modèle cognitif
[Termes descripteurs IGN] transformation géométriqueRésumé : (Auteur) In everyday communication, people effortlessly translate between spatial cognitive frames of reference. For example, a tourist guide translates from a map (“the fountain is north‐west of the church”) into a cognitive frame for a tourist (“the fountain in front of the church”). While different types of cognitive reference frames and their relevance for language cultures have been studied in considerable depth, we still lack adequate transformation models. In this article, we argue that transformations in current Geographic Information Systems (GIS) are inappropriate to this end. Appropriate transformation models need to go beyond point discretization to take into account vague transformations, in order to deal with forms, sizes, and vagueness of spatial relations relative to ground objects. We argue that neural fields should be used to denote fuzzy positions, directions, and sizes in a particular frame. We propose fuzzy vector spaces to approximate neural field behavior with affine transformations, including fuzzy translation, rotation, and scaling, in order to efficiently transform between different cognitive perspectives. We use an implementation in Haskell to describe a geographic map from the perspective of six well‐known cognitive frames of reference. Based on these findings, we give an outlook on the principles of a “neural GIS.” Numéro de notice : A2018-570 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12318 date de publication en ligne : 11/10/2018 En ligne : https://doi.org/10.1111/tgis.12318 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92289
in Transactions in GIS > vol 22 n° 5 (October 2018) . - pp 1083 - 1104[article]Modeling spatiotemporal information generation / Simon Scheider in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
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Titre : Modeling spatiotemporal information generation Type de document : Article/Communication Auteurs : Simon Scheider, Auteur ; Benedikt Gräler, Auteur ; Edzer J. Pebesma, Auteur ; Christophe Stasch, Auteur Année de publication : 2016 Article en page(s) : pp 1980 - 2008 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes descripteurs IGN] base de données dérivée
[Termes descripteurs IGN] données hétérogènes
[Termes descripteurs IGN] exploration de données géographiques
[Termes descripteurs IGN] information géographique
[Termes descripteurs IGN] mise à jour de base de données
[Termes descripteurs IGN] mise à jour en continu
[Termes descripteurs IGN] regroupement de données
[Termes descripteurs IGN] source de donnéesRésumé : (Auteur) Maintaining knowledge about the provenance of datasets, that is, about how they were obtained, is crucial for their further use. Contrary to what the overused metaphors of ‘data mining’ and ‘big data’ are implying, it is hardly possible to use data in a meaningful way if information about sources and types of conversions is discarded in the process of data gathering. A generative model of spatiotemporal information could not only help automating the description of derivation processes but also assessing the scope of a dataset’s future use by exploring possible transformations. Even though there are technical approaches to document data provenance, models for describing how spatiotemporal data are generated are still missing. To fill this gap, we introduce an algebra that models data generation and describes how datasets are derived, in terms of types of reference systems. We illustrate its versatility by applying it to a number of derivation scenarios, ranging from field aggregation to trajectory generation, and discuss its potential for retrieval, analysis support systems, as well as for assessing the space of meaningful computations. Numéro de notice : A2016-573 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1080/13658816.2016.1151520 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81729
in International journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 1980 - 2008[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve 3L Disponible Towards sustainable mobility behavior: research challenges for location-aware information and communication technology / Paul Weiser in Geoinformatica [en ligne], vol 20 n° 2 (April - June 2016)
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Titre : Towards sustainable mobility behavior: research challenges for location-aware information and communication technology Type de document : Article/Communication Auteurs : Paul Weiser, Auteur ; Simon Scheider, Auteur ; Dominik Bucher, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 213 - 239 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes descripteurs IGN] approche participative
[Termes descripteurs IGN] changement climatique
[Termes descripteurs IGN] comportement
[Termes descripteurs IGN] développement durable
[Termes descripteurs IGN] état de l'art
[Termes descripteurs IGN] innovation technologique
[Termes descripteurs IGN] mobilité
[Termes descripteurs IGN] positionnement cinématique
[Termes descripteurs IGN] système d'information géographique
[Termes descripteurs IGN] téléphonie mobile
[Termes descripteurs IGN] transportRésumé : (auteur) Private transport accounts for a large amount of total CO2 emissions, thus significantly contributing to global warming. Tools that actively support people in engaging in a more sustainable life-style without restricting their mobility are urgently needed. How can location-aware information and communication technology (ICT) enable novel interactive and participatory approaches that help people in becoming more sustainable? In this survey paper, we discuss the different aspects of this challenge from a technological and cognitive engineering perspective, based on an overview of the main information processes that may influence mobility behavior. We review the state-of-the-art of research with respect to various ways of influencing mobility behavior (e.g., through providing real-time, user-specific, and location-based feedback) and suggest a corresponding research agenda. We conclude that future research has to focus on reflecting individual goals in providing personal feedback and recommendations that take into account different motivational stages. In addition, a long-term and large-scale empirical evaluation of such tools is necessary. Numéro de notice : A2016-372 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article En ligne : http://dx.doi.org/10.1007/s10707-015-0242-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81137
in Geoinformatica [en ligne] > vol 20 n° 2 (April - June 2016) . - pp 213 - 239[article]