A review of volunteered geographic information quality assessment methods

Senaratne, Hansi; Mobasheri, Amin; Ali, Ahmed Loai; Capineri, Cristina; Haklay, Muki

doi:10.1080/13658816.2016.1189556

Cited by 365 publications

(327 citation statements)

References 70 publications

Supporting

Mentioning

315

Contrasting

Unclassified

Order By: Relevance

“…Many methods have then been proposed to assess VGI quality; a review can be found in [4][5][6], among others. The quality assessment of VGI POIs is essential as many applications are based on such data, and can be affected by low-quality POIs.…”

Section: Introductionmentioning

confidence: 99%

Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations

Touya¹,

Antoniou²,

Olteanu‐Raimond³

et al. 2017

IJGI

View full text Add to dashboard Cite

Abstract:With the development of location-aware devices and the success and high use of Web 2.0 techniques, citizens are able to act as sensors by contributing geographic information. In this context, data quality is an important aspect that should be taken into account when using this source of data for different purposes. The goal of the paper is to analyze the quality of crowdsourced data and to study its evolution over time. We propose two types of approaches: (1) use the intrinsic characteristics of the crowdsourced datasets; or (2) evaluate crowdsourced Points of Interest (POIs) using external datasets (i.e., authoritative reference or other crowdsourced datasets), and two different methods for each approach. The potential of the combination of these approaches is then demonstrated, to overcome the limitations associated with each individual method. In this paper, we focus on POIs and places coming from the very successful crowdsourcing project: OpenStreetMap. The results show that the proposed approaches are complementary in assessing data quality. The positive results obtained for data matching show that the analysis of data quality through automatic data matching is possible but considerable effort and attention are needed for schema matching given the heterogeneity of OSM and the representation of authoritative datasets. For the features studied, it can be noted that change over time is sometimes due to disagreements between contributors, but in most cases the change improves the quality of the data.

show abstract

Section: Introductionmentioning

confidence: 99%

Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations

Touya¹,

Antoniou²,

Olteanu‐Raimond³

et al. 2017

IJGI

View full text Add to dashboard Cite

show abstract

“…However, very few studies have reported on the fitness-of-use of the dataset in developing countries [56,[90][91][92][93] using established quality indicators. The established methods are unsuitable to assess OSM data quality in the case of the non-availability of authoritative data [14]. Hence, assessment through intrinsic quality indicators would certainly encourage researchers to have a deeper understanding of datasets.…”

Section: Semantic Accuracymentioning

confidence: 99%

Assessing OpenStreetMap Data Using Intrinsic Quality Indicators: An Extension to the QGIS Processing Toolbox

Sehra

Singh

2017

Future Internet

View full text Add to dashboard Cite

OpenStreetMap (OSM) is a recent emerging area in computational science. There are several unexplored issues in the quality assessment of OSM. Firstly, researchers are using various established assessment methods by comparing OSM with authoritative dataset. However, these methods are unsuitable to assess OSM data quality in the case of the non-availability of authoritative data. In such a scenario, the intrinsic quality indicators can be used to assess the quality. Secondly, a framework for data assessment specific to different geographic information system (GIS) domains is not available. In this light, the current study presents an extension of the Quantum GIS (QGIS) processing toolbox by using existing functionalities and writing new scripts to handle spatial data. This would enable researchers to assess the completeness of spatial data using intrinsic indicators. The study also proposed a heuristic approach to test the road navigability of OSM data. The developed models are applied on Punjab (India) OSM data. The results suggest that the OSM project in Punjab (India) is progressing at a slow peace, and contributors' motivation is required to enhance the fitness of data. It is concluded that the scripts developed to provide an intuitive method to assess the OSM data based on quality indicators can be easily utilized for evaluating the fitness-of-use of the data of any region.

show abstract

“…), completeness, thematic similarity, and logical consistency of VGI with authoritative data from NMAs and CSC [5,[17][18][19][20]. For a complete review of data quality assessment methods, see [21]. However, there has been little work documented in the literature in how VGI is actually collected "in the field".…”

Section: Motivationmentioning

confidence: 99%

“…There are many differences in how NMAs and CSC collect, analyse, manage and distribute geographic information to that of VGI projects. NMAs and CSC use robust and standardised protocols considered as "terrain nominal" (i.e., an abstract concept defined by a cartographic representation perfectly compliant with data specification) [21], which govern and guide their collection of geographic data. Whilst VGI projects often provide guidelines to their contributors on how to collect and survey geographic data, these guidelines are often flexible and can lack professional geographical survey rigour.…”

Section: Motivationmentioning

confidence: 99%

Towards a Protocol for the Collection of VGI Vector Data

Mooney

Minghini²,

Laakso

et al. 2016

IJGI

View full text Add to dashboard Cite

Abstract:A protocol for the collection of vector data in Volunteered Geographic Information (VGI) projects is proposed. VGI is a source of crowdsourced geographic data and information which is comparable, and in some cases better, than equivalent data from National Mapping Agencies (NMAs) and Commercial Surveying Companies (CSC). However, there are many differences in how NMAs and CSC collect, analyse, manage and distribute geographic information to that of VGI projects. NMAs and CSC make use of robust and standardised data collection protocols whilst VGI projects often provide guidelines rather than rigorous data collection specifications. The proposed protocol addresses formalising the collection and creation of vector data in VGI projects in three principal ways: by manual vectorisation; field survey; and reuse of existing data sources. This protocol is intended to be generic rather than being linked to any specific VGI project. We believe that this is the first protocol for VGI vector data collection that has been formally described in the literature. Consequently, this paper shall serve as a starting point for on-going development and refinement of the protocol.

show abstract

A review of volunteered geographic information quality assessment methods

Cited by 365 publications

References 70 publications

Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations

Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations

Assessing OpenStreetMap Data Using Intrinsic Quality Indicators: An Extension to the QGIS Processing Toolbox

Towards a Protocol for the Collection of VGI Vector Data

Contact Info

Product

Resources

About