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Auteur Franck O. Ostermann |
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Affiner la recherche Interroger des sources externesReproducible research and GIScience: An evaluation using GIScience conference papers / Franck O. Ostermann (2021)
Titre : Reproducible research and GIScience: An evaluation using GIScience conference papers Type de document : Article/Communication Auteurs : Franck O. Ostermann, Auteur ; Daniel Nüst, Auteur ; Carlos Granell, Auteur ; Barbara Hofer, Auteur ; Markus Konkol, Auteur Editeur : Leibniz [Allemagne] : Schloss Dagstuhl – Leibniz-Zentrum für Informatik Année de publication : 2021 Conférence : GIScience 2021, 11th International Conference on Geographic Information Science 27/09/2021 30/09/2021 Poznań Pologne Open Access Proceedings Importance : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Société de l'information
[Termes IGN] code source libre
[Termes IGN] données ouvertes
[Termes IGN] information géographique
[Termes IGN] recherche scientifique
[Termes IGN] reproductibilitéRésumé : (auteur) GIScience conference authors and researchers face the same computational reproducibility challenges as authors and researchers from other disciplines who use computers to analyse data. Here, to assess the reproducibility of GIScience research, we apply a rubric for assessing the reproducibility of 75 conference papers published at the GIScience conference series in the years 2012-2018. Since the rubric and process were previously applied to the publications of the AGILE conference series, this paper itself is an attempt to replicate that analysis, however going beyond the previous work by evaluating and discussing proposed measures to improve reproducibility in the specific context of the GIScience conference series. The results of the GIScience paper assessment are in line with previous findings: although descriptions of workflows and the inclusion of the data and software suffice to explain the presented work, in most published papers they do not allow a third party to reproduce the results and findings with a reasonable effort. We summarise and adapt previous recommendations for improving this situation and propose the GIScience community to start a broad discussion on the reusability, quality, and openness of its research. Further, we critically reflect on the process of assessing paper reproducibility, and provide suggestions for improving future assessments. The code and data for this article are published at https://doi.org/10.5281/zenodo.4032875. Numéro de notice : C2021-080 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/INFORMATIQUE/SOCIETE NUMERIQUE Nature : Communication DOI : 10.4230/LIPIcs.GIScience.2021.II.2 Date de publication en ligne : 14/09/2021 En ligne : https://doi.org/10.4230/LIPIcs.GIScience.2021.II.2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100938
Titre : Modeling aggregated expertise of user contributions to assess the credibility of OpenStreetMap features Type de document : Article/Communication Auteurs : Bani Idham Muttaqien, Auteur ; Franck O. Ostermann, Auteur ; Robert Lemmens, Auteur Année de publication : 2018 Article en page(s) : pp 823 - 841 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données localisées des bénévoles
[Termes IGN] expertise
[Termes IGN] fiabilité des données
[Termes IGN] OpenStreetMap
[Termes IGN] qualité des données
[Termes IGN] utilisateur civilRésumé : (Auteur) The emergence of volunteered geographic information (VGI) during the past decade has fueled a wide range of research and applications. The assessment of VGI quality and fitness‐of‐use is still a challenge because of the non‐standardized and crowdsourced data collection process, as well as the unknown skill and motivation of the contributors. However, the frequent approach of assessing VGI quality against external data sources using ISO quality standard measures is problematic because of a frequent lack of available external (reference) data, and because for certain types of features, VGI might be more up‐to‐date than the reference data. Therefore, a VGI‐intrinsic measure of quality is highly desirable. This study proposes such an intrinsic measure of quality by developing the concept of aggregated expertise based on the characteristics of a feature's contributors. The article further operationalizes this concept and examines its feasibility through a case study using OpenStreetMap (OSM). The comparison of model OSM feature quality with information from a field survey demonstrates the successful implementation of this novel approach. Numéro de notice : A2018-580 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12454 Date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1111/tgis.12454 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92328
in Transactions in GIS > vol 22 n° 3 (June 2018) . - pp 823 - 841[article]
Titre : Advancing science with VGI: Reproducibility and replicability of recent studies Type de document : Article/Communication Auteurs : Franck O. Ostermann, Auteur ; Carlos Granell, Auteur Année de publication : 2017 Article en page(s) : pp 224 – 237 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] diffusion de données
[Termes IGN] données localisées des bénévoles
[Termes IGN] gestion de crise
[Termes IGN] réplication
[Termes IGN] source de données
[Termes IGN] test de performanceRésumé : (auteur) In scientific research, reproducibility and replicability are requirements to ensure the advancement of our body of knowledge. This holds true also for VGI-related research and studies. However, the characteristics of VGI suggest particular difficulties in ensuring reproducibility and replicability. In this article, we aim to examine the current situation in VGI-related research, and identify strategies to ensure realization of its full potential. To do so, we first investigate the different aspects of reproducibility and replicability and their impact on VGI-related research. These impacts are different depending on the objectives of the study. Therefore, we examine the study focus of VGI-related research to assess the current body of research and structure our assessment. This work is based on a rigorous review of the elements of reproducibility and a systematic mapping and analysis of 58 papers on the use of VGI in the crisis management field. Results of our investigation show that reproducibility issues related to data are a serious concern, while reproducibility issues related to analysis methods and processes face fewer challenges. However, since most studies still focus on analyzing the source data, reproducibility and replicability are still an unsolved problem in VGI-related research. Therefore, we show initiatives tackling the problem, and finally formulate strategies to improve the situation. Numéro de notice : A2017-164 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12195 En ligne : http://dx.doi.org/10.1111/tgis.12195 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84698
in Transactions in GIS > vol 21 n° 2 (April 2017) . - pp 224 – 237[article]
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
- European handbook of crowdsourced geographic information, ch. 8. Quality analysis of the Parisian OSM toponyms evolution / Vyron Antoniou (2016)
- 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)
- European handbook of crowdsourced geographic information, ch. 14. Querying VGI by semantic enrichment / Robert Lemmens (2016)
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