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European handbook of crowdsourced geographic information / Cristina Capineri (2016)

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Titre :	European handbook of crowdsourced geographic information
Type de document :	Monographie
Auteurs :	Cristina Capineri, Éditeur scientifique ; Muki M. Haklay, Éditeur scientifique ; Haosheng Huang, Éditeur scientifique ; Vyron Antoniou, Éditeur scientifique ; Juhani Kettunen, Éditeur scientifique ; Franck O. Ostermann, Éditeur scientifique ; Ross S. Purves, Éditeur scientifique
Editeur :	Londres : Ubiquity press
Année de publication :	2016
Importance :	476 p.
Format :	21 x 30 cm
ISBN/ISSN/EAN :	978-1-909188-80-8
Langues :	Anglais (eng)
Note de contenu :	Chapter 1. Introduction Part I: Theoretical and social aspects Chapter 2. The nature of volunteered geographic information (Cristina Capineri) Chapter 3. Why is participation inequality important? (Mordechai (Muki) Haklay) Chapter 4. Social Media Geographic Information: Why social is special when it goes spatial? (Michele Campagna) Part II: Quality: Criteria and methodologies Chapter 5. Handling quality in crowdsourced geographic information (Laura Criscuolo, Paola Carrara, Gloria Bordogna, Monica Pepe, Francesco Zucca, Roberto Seppi, Alessandro Oggioni and Anna Rampini) Chapter 6. Data quality in crowdsourcing for biodiversity research: issues and examples (Clemens Jacobs) Chapter 7. Semantic Challenges for Volunteered Geographic Information (Andrea Ballatore) Chapter 8. Quality analysis of the Parisian OSM toponyms evolution (Vyron Antoniou, Guillaume Touya and Ana-Maria Raimond) Chapter 9. Tackling the thematic accuracy of areal features in OpenStreetMap (Ahmed Loai Ali) Chapter 10. Enhancing the management of quality of VGI: contributions from context and task modelling (Benedicte Bucher, Gilles Falquet, Claudine Metral and Rob Lemmens) Part III: Data analytics Chapter 11. A methodological toolbox for exploring collections of textually annotated georeferenced photographs (Ross S. Purves and William A. Mackaness) Chapter 12. Gaining Knowledge from Georeferenced Social Media Data with Visual Analytics (Gennady Andrienko and Natalia Andrienko) Chapter 13. Head/tail Breaks for Visualization of City Structure and Dynamics (Bin Jiang) Chapter 14. Querying VGI by semantic enrichment (Rob Lemmens, Gilles Falquet, Stefano De Sabbata, Bin Jiang and Benedicte Bucher) Chapter 15. Extracting Location Information from Crowd-sourced Social Network Data (Pinar Karagoz, Halit Oguztuzun, Ruket Cakici, Ozer Ozdikis, Kezban Dilek Onal and Meryem Sagcan) Chapter 16. Spatial and Temporal Sentiment Analysis of Twitter data (Zhiwen Song and Jianhong (Cecilia) Xia) Chapter 17. Social Networks VGI: Twitter Sentiment Analysis of Social Hotspots (Dario Stojanovski, Ivan Chorbev, Ivica Dimitrovski and Gjorgji Madjarov) Chapter 18. Research on social media feeds – A GIScience perspective (Enrico Steiger, Rene Westerholt and Alexander Zipf) Part IV: VGI and crowdsourcing in environmental monitoring Chapter 19. Changing role of citizens in the national environmental monitoring (Juhani Kettunen, Jari Silander, Matti Lindholm, Maiju Lehtiniemi, Outi Setälä and Seppo Kaitala) Chapter 20. On the contribution of Volunteered Geographic Information to land monitoring efforts (Jamal Jokar Arsanjani and Cidália C. Fonte) Chapter 21. Discussing the potential of crowdsourced geographic information for urban areas monitoring using the panoramio initiative (Flavio Lupia and Jacinto Estima) Chapter 22. AtrapaelTigre.com: enlisting citizen-scientists in the war on tiger mosquitoes (Aitana Oltra, John R.B. Palmer and Frederic Bartumeus) Chapter 23. Crowdsourcing geographic information for disaster risk management and improving urban resilience: an overview of the lessons learned (João Porto de Albuquerque, Melanie Eckle, Benjamin Herfort and Alexander Zipf) Part V: VGI in mobility Chapter 24. Crowdsourcing for individual needs - the case of routing and navigation for mobility-impaired persons (Alexander Zipf, Amin Mobasheri, Adam Rousell and Stefan Hahmann) Chapter 25. Smart Timetable Service Based on Crowdsensed Data (Károly Farkas) Chapter 26. Mobile crowd-sensing in the Smart City (Imre Lendák) Chapter 27. Mobile crowd sensing for smart urban mobility (Dragan Stojanovic, Bratislav Predic and Natalija Stojanovic) Part VI: VGI in spatial planning Chapter 28. Using mobile crowdsourcing and geotagged social media data to study people’s affective responses to environments (Haosheng Huang and Georg Gartner) Chapter 29. Integrating Authoritative and Volunteered Geographic Information for spatial planning (Pierangelo Massa and Michele Campagna) Chapter 30. A Proposed Crowdsourcing Cadastral Model: Taking Advantage of Previous Experience and Innovative Techniques (Sofia Basiouka and Chryssy Potsiou) Chapter 31. Modelling the world in 3D from VGI/Crowdsourced data (Hongchao Fan and Alexander Zipf) Glossary (Linda See, Cristina Capineri and Sofia Basiouka)
Numéro de notice :	17356
Affiliation des auteurs :	non IGN
Thématique :	GEOMATIQUE
Nature :	Recueil / ouvrage collectif
DOI :	10.5334/bax
En ligne :	https://doi.org/10.5334/bax
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=83781

Contient

European handbook of crowdsourced geographic information, ch. 8. Quality analysis of the Parisian OSM toponyms evolution / Vyron Antoniou (2016)

Public

contenu dans European handbook of crowdsourced geographic information / Cristina Capineri (2016)

Titre de série :	European handbook of crowdsourced geographic information, ch. 8
Titre :	Quality analysis of the Parisian OSM toponyms evolution
Type de document :	Chapitre/Contribution
Auteurs :	Vyron Antoniou, Auteur ; Guillaume Touya , Auteur ; Ana-Maria Olteanu-Raimond , Auteur
Editeur :	Londres : Ubiquity press
Année de publication :	2016
Projets :	ENERGIC / Capineri, Cristina
Importance :	pp 97 - 112
Note générale :	bibliographie
Langues :	Français (fre)
Descripteur :	[Vedettes matières IGN] Toponymie [Termes IGN] données localisées des bénévoles [Termes IGN] OpenStreetMap [Termes IGN] Paris (75) [Termes IGN] qualité des données [Termes IGN] répertoire toponymique [Termes IGN] toponyme
Résumé :	(auteur) The paper presents empirical research on the quality of the toponyms that can be retrieved from OpenStreetMap (OSM) under the purpose of enriching authoritative toponymic databases and gazetteers. An analysis on the volatility of places and points-of-interest (POIs) is presented. We examine how named features behave and change in terms of type, name and location. The challenge is to understand the behavior and consequently the fitness-for-purpose of OSM data when it comes to a possible use and integration with authoritative datasets. We show that, depending on the OSM feature type, the volatility can vary considerably and we elucidate which feature types are consistent, and thus could be used in authoritative gazetteers despite their grassroots nature and if there are spatial patterns behind the location changes of features during their lifespan.
Numéro de notice :	H2016-001
Affiliation des auteurs :	LASTIG COGIT+Ext (2012-2019)
Thématique :	GEOMATIQUE/TOPONYMIE
Nature :	Chapître / contribution
nature-HAL :	ChOuvrScient
DOI :	10.5334/bax
En ligne :	https://doi.org/10.5334/bax
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=83782

Documents numériques

Quality analysis of the Parisian OSM toponyms evolution

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European handbook of crowdsourced geographic information, ch. 10. Enhancing the management of quality of VGI: contributions from context and task modelling / Bénédicte Bucher (2016)

European handbook of crowdsourced geographic information, ch. 12. Gaining knowledge from georeferenced social media data with visual analytics / Gennady Andrienko (2016)

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contenu dans European handbook of crowdsourced geographic information / Cristina Capineri (2016)

Titre de série :	European handbook of crowdsourced geographic information, ch. 12
Titre :	Gaining knowledge from georeferenced social media data with visual analytics
Type de document :	Chapitre/Contribution
Auteurs :	Gennady Andrienko, Auteur ; Natalia Andrienko, Auteur
Editeur :	Londres : Ubiquity press
Année de publication :	2016
Importance :	pp 157 - 167
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Termes IGN] analyse de groupement [Termes IGN] analyse géovisuelle [Termes IGN] analyse spatiale [Termes IGN] données spatiotemporelles [Termes IGN] mobilité urbaine [Termes IGN] réseau social [Termes IGN] trajet (mobilité) [Vedettes matières IGN] Géovisualisation
Résumé :	(auteur) Analysis of the collections of geographically referenced posts published in social media, such as Twitter, Flickr, and YouTube, can bring new knowledge about places, geographical objects, and events interesting to people, and about people’s mobility behaviours. Gaining knowledge from large data collections requires combining computational analysis with human interpretation, judgement, and reasoning, which, in turn, require appropriate visual representations of the data and analysis results. Visual analytics integrates computational analysis techniques with interactive visual interfaces to support collaborative human−computer analytical activities. We give a brief overview of visual analytics approaches to extracting various kinds of information and knowledge from georeferenced social media data.
Numéro de notice :	H2016-003
Affiliation des auteurs :	non IGN
Thématique :	GEOMATIQUE/URBANISME
Nature :	Chapître / contribution
nature-HAL :	ChOuvrScient
DOI :	10.5334/bax
En ligne :	https://doi.org/10.5334/bax
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=83785

Documents numériques

Gaining knowledge from georeferenced social media data

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European handbook of crowdsourced geographic information, ch. 14. Querying VGI by semantic enrichment / Robert Lemmens (2016)

Documents numériques

European handbook of crowdsourced geographic information

Adobe Acrobat PDF

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