Analysis of collaboration networks in OpenStreetMap through weighted social multigraph mining

Truong, Quy Thy; Runz, Cyril de; Touya, Guillaume

doi:10.1080/13658816.2018.1556395

Cited by 15 publications

(12 citation statements)

References 31 publications

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“…Having a better understanding of the quality of VGI may help the adoption of crowdsourced geospatial data in some projects as the perception of unreliability may impede the adoption. To address the issues on trust, transparency and reliability Truong et al (2018) looked at the contributors behaviour and their interactions. They qualified the behaviour of contributors to OpenStreetMap (OSM) through a multigraph approach to reproduce contributor's interactions in a more comprehensive way.…”

Section: Vgi Data Quality Issuesmentioning

confidence: 99%

“…This editorial highlights how these issues are discussed and addressed by the articles of this special issue and how the papers highlight emerging technologies, concepts, platforms, debates, and methodologies and techniques within VGI and suggest future research directions. This special issue gathered papers on the topics of crowdsourced geospatial data quality (Ballatore and Arsanjani 2018), thematic uncertainty and consistency across data sources (Hervey and Kuhn 2018), spatial biases (Millar et al, 2018), trust issues within VGI (Severinsen et al 2019), and contributors behaviour and interactions (Truong et al 2018).…”

Section: Introductionmentioning

confidence: 99%

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Crowdsourced geospatial data quality: challenges and future directions

Basiri

Haklay

Foody

et al. 2019

International Journal of Geographical Information Science

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Section: Vgi Data Quality Issuesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Crowdsourced geospatial data quality: challenges and future directions

Basiri

Haklay

Foody

et al. 2019

International Journal of Geographical Information Science

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“…The study of past vandalism cases showed the contribution patterns, and the behaviour of the contributor in the OSM platform was key to identify these cases [5,6,9], so we included some contributor information in our corpus and decided to add fake users as contributors of the fake vandalism. The contributors can be characterised by their age in the project [9,20], their number of past contributions [14,21], or by their interactions with other OSM users [22,23]. These measures can be computed for existing contributors, but for fake contributors, the ones based on the analysis of the interactions with the other users are very complex to simulate.…”

Section: Vandalizing the Datasetmentioning

confidence: 99%

OSMWatchman: Learning How to Detect Vandalized Contributions in OSM Using a Random Forest Classifier

Truong

Touya

Runz

2020

IJGI

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Though Volunteered Geographic Information (VGI) has the advantage of providing free open spatial data, it is prone to vandalism, which may heavily decrease the quality of these data. Therefore, detecting vandalism in VGI may constitute a first way of assessing the data in order to improve their quality. This article explores the ability of supervised machine learning approaches to detect vandalism in OpenStreetMap (OSM) in an automated way. For this purpose, our work includes the construction of a corpus of vandalism data, given that no OSM vandalism corpus is available so far. Then, we investigate the ability of random forest methods to detect vandalism on the created corpus. Experimental results show that random forest classifiers perform well in detecting vandalism in the same geographical regions that were used for training the model and has more issues with vandalism detection in “unfamiliar regions”.

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“…Для этого слой сохраняется в «shape» файл или в БД, и в качестве параметра выбирается новая система. Но при выводе проекта на экран все слои приводят в единую координатную плоскость [5][6][7].…”

Section: методология применения инструментария гис для управления труunclassified

Methodological Aspects for the Use of GIS Tools for Managing the Employment of Graduates

Kadirova

2019

JIT

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The purpose of this study is to improve the mechanism of employment of graduates of universities in the field in the region with the use of modern computer technology. Namely, the article discusses the advantages and methodological aspects of using the tools of geographic information systems, which are a symbiosis of the management capabilities of large databases and spatial visualization characteristic of topographic maps by using QGIS A relational database table or a spreadsheet with a geolocation field, which allows data to be placed on a map, represents each information layer. The scientific significance of the article is due to the fact that this technology contributes to the creation of a single information space of the employers market in the context of popular specialties, as well as to the active establishment of cooperation between universities and employers in order to improve the mechanism of employment of graduates on the bases of competence-based approach. The result of the research is the methodological aspects of the use of open geographic information system QGIS for managing the employment of young professionals. In addition, tasks have been set for the mechanism for applying geo-information technologies in the employment of university graduates.

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Analysis of collaboration networks in OpenStreetMap through weighted social multigraph mining

Cited by 15 publications

References 31 publications

Crowdsourced geospatial data quality: challenges and future directions

Crowdsourced geospatial data quality: challenges and future directions

OSMWatchman: Learning How to Detect Vandalized Contributions in OSM Using a Random Forest Classifier

Methodological Aspects for the Use of GIS Tools for Managing the Employment of Graduates

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