Within volunteered geographic information (VGI), citizen science stands out as a class of activities that require special attention and analysis. Citizen science is likely to be the longest running of VGI activities, with some projects showing continuous effort over a century. In addition, many projects are characterised by a genuine element of volunteering and contribution of information for the benefit of human knowledge and science. They are also tasks where data quality and uncertainty come to the fore when evaluating the validity of the results. This chapter provides an overview of citizen science in the context of VGI – hence the focus on geographic citizen science. This chapter highlights the historical context of citizen science and its more recent incarnation. It also covers some of the cultural and conceptual challenges that citizen science faces and the resulting limitation on the level of engagement. By drawing parallels with the Participatory Geographic Information Systems (PGIS) literature, the chapter offers a framework for participation in citizen science and concludes with the suggestion that a more participatory mode of citizen science is possible.

Citizen Science and Volunteered Geographic Information: Overview and Typology of Participation

Urban scholars have studied street networks in various ways, but there are data availability and consistency limitations to the current urban planning/street network analysis literature. To address these challenges, this article presents OSMnx, a new tool to make the collection of data and creation and analysis of street networks simple, consistent, automatable and sound from the perspectives of graph theory, transportation, and urban design. OSMnx contributes five significant capabilities for researchers and practitioners: first, the automated downloading of political boundaries and building footprints; second, the tailored and automated downloading and constructing of street network data from OpenStreetMap; third, the algorithmic correction of network topology; fourth, the ability to save street networks to disk as shapefiles, GraphML, or SVG files; and fifth, the ability to analyze street networks, including calculating routes, projecting and visualizing networks, and calculating metric and topological measures. These measures include those common in urban design and transportation studies, as well as advanced measures of the structure and topology of the network. Finally, this article presents a simple case study using OSMnx to construct and analyze street networks in Portland, Oregon.

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OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks

Volunteered geographic information (VGI) is a phenomenon of recent years, offering an alternative mechanism for the acquisition and compilation of geographic information. As such it offers substantial advantages, but suffers from a general lack of quality assurance. We discuss the issues involved in the determination of quality for geospatial data, and trace the history of research on VGI quality. We describe three approaches to quality assurance, which we term the crowd-sourcing, social, and geographic approaches respectively. We discuss the advantages and limitations of each, and the research that will be needed to operationalize the geographic approach.

Assuring the quality of volunteered geographic information

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OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks

With the ubiquity of advanced web technologies and location-sensing hand held devices, citizens regardless of their knowledge or expertise, are able to produce spatial information. This phenomenon is known as volunteered geographic information VGI. During the past decade VGI has been used as a data source supporting a wide range of services, such as environmental monitoring, events reporting, human movement analysis, disaster management, etc. However, these volunteer-contributed data also come with varying quality. Reasons for this are: data is produced by heterogeneous contributors, using various technologies and tools, having different level of details and precision, serving heterogeneous purposes, and a lack of gatekeepers. Crowd-sourcing, social, and geographic approaches have been proposed and later followed to develop appropriate methods to assess the quality measures and indicators of VGI. In this article, we review various quality measures and indicators for selected types of VGI and existing quality assessment methods. As an outcome, the article presents a classification of VGI with current methods utilized to assess the quality of selected types of VGI. Through these findings, we introduce data mining as an additional approach for quality handling in VGI.

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A review of volunteered geographic information quality assessment methods

The concept of Volunteered Geographic Information (VGI) has recently emerged from the new Web 2.0 technologies. The OpenStreetMap project is currently the most significant example of a system based on VGI. It aims at producing free vector geographic databases using contributions from Internet users. Spatial data quality becomes a key consideration in this context of freely downloadable geographic databases. This article studies the quality of French OpenStreetMap data. It extends the work of Haklay to France, provides a larger set of spatial data quality element assessments (i.e. geometric, attribute, semantic and temporal accuracy, logical consistency, completeness, lineage, and usage), and uses different methods of quality control. The outcome of the study raises questions such as the heterogeneity of processes, scales of production, and the compliance to standardized and accepted specifications. In order to improve data quality, a balance has to be struck between the contributors' freedom and their respect of specifications. The development of appropriate solutions to provide this balance is an important research issue in the domain of user-generated content.

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Quality Assessment of the French OpenStreetMap Dataset

Little by little, co-existing geographical data sets are integrated into multi-representation databases, where the data sets represent different level of detail, or different point of views for the...

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ScaleMaster 2.0: a ScaleMaster extension to monitor automatic multi-scales generalizations

https://hal.archives-ouvertes.fr/hal-02288803/document

Cartographic Generalisation Aware of Multiple Representations

Les nouvelles technologies du Web 2.0 ont permis l'emergence des contenus crees collaborativement dont l'exemple le plus interessant est le projet OpenStreetMap. Ce projet vise a produire une base de donnees topographiques entierement libre. Cet article etudie la qualite des donnees francaises de ce projet en prenant comme comparaison des donnees de l'Institut Geographique National. La qualite des donnees est tres heterogene du fait de l'absence de specifications precises et acceptees. ABSTRACT. New concepts like free data or Volunteered Geographic Information recently emerged thanks to new Web 2.0 technologies. The OpenStreetMap project is the most significant example. It aims at producing free vector topographic databases. This paper studies the OpenStreetMap french data quality compared to institutional databases of the french NMA. Data Quality is quite heterogeneous due to a lack of precise and well-accepted specifications.

Jean-François Girres

Papers

Quality Assessment of the French OpenStreetMap Dataset

ScaleMaster 2.0: a ScaleMaster extension to monitor automatic multi-scales generalizations

Cartographic Generalisation Aware of Multiple Representations

Première évaluation de la qualité des données libres d'OpenStreetMap en France