On predicting and improving the quality of Volunteer Geographic Information projects

Bordogna, Gloria; Carrara, Paola; Criscuolo, Laura; Pepe, Monica; Rampini, A.

doi:10.1080/17538947.2014.976774

Cited by 42 publications

(50 citation statements)

References 23 publications

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“…Introducing overly burdensome structures to ensure quality could damage the potential contributions from related socially-conscious and citizen-focused data collection and mapping efforts. A review is provided in Reference [65] of the distinct types of citizen science projects and the expectations on the quality of the information they deal with, and in particular the quality of crowdsourced geographic information in those projects. They go on to propose an innovative model based on linguistic decision making for assessing the quality of a crowdsourced geographic information database created in citizen science projects.…”

Section: Quality and Use Of The Data For Researchmentioning

confidence: 99%

Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information

See

Mooney

Foody

et al. 2016

IJGI

350

235

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Citizens are increasingly becoming an important source of geographic information, sometimes entering domains that had until recently been the exclusive realm of authoritative agencies. This activity has a very diverse character as it can, amongst other things, be active or passive, involve spatial or aspatial data and the data provided can be variable in terms of key attributes such as format, description and quality. Unsurprisingly, therefore, there are a variety of terms used to describe data arising from citizens. In this article, the expressions used to describe citizen sensing of geographic information are reviewed and their use over time explored, prior to categorizing them and highlighting key issues in the current state of the subject. The latter involved a review of 100 Internet sites with particular focus on their thematic topic, the nature of the data and issues such as incentives for contributors. This review suggests that most sites involve active rather than passive contribution, with citizens typically motivated by the desire to aid a worthy cause, often receiving little training. As such, this article provides a snapshot of the role of citizens in crowdsourcing geographic information and a guide to the current status of this rapidly emerging and evolving subject.

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Section: Quality and Use Of The Data For Researchmentioning

confidence: 99%

Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information

See

Mooney

Foody

et al. 2016

IJGI

350

235

View full text Add to dashboard Cite

show abstract

“…Even after the publication of data on the web, mechanisms for enabling users for a collaborative revision can be employed to flag, comment on, and improve contributions. A more detailed description of the ex-ante and ex-post strategies can be found in reference [25,26], while an important analysis of their application in CS projects dates back to 2011 [27]. An interesting aspect of these technologies is the role of the one entrusted for controlling quality.…”

Section: Qualification/validationmentioning

confidence: 99%

CS Projects Involving Geoinformatics: A Survey of Implementation Approaches

Criscuolo¹,

Bordogna²,

Carrara³

et al. 2018

IJGI

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Abstract:In the last decade, citizen science (CS) has seen a renewed interest from both traditional science and the lay public as testified by a wide number of initiatives, projects, and dedicated technological applications. One of the main reasons for this renewed interest lies in the fact that the ways in which citizen science projects are designed and managed have been significantly improved by the recent advancements in information and communications technologies (ICT), especially in the field of geoinformatics. In this research work, we investigate currently active citizen science projects that involve geoinformation to understand how geoinformatics is actually employed. To achieve this, we define eight activities typically carried out during the implementation of a CS initiative as well as a series of approaches for each activity, in order to pinpoint distinct strategies within the different projects. To this end, a representative set of ongoing CS initiatives is selected and surveyed. The results show how CS projects address the various activities, and report which strategies and technologies from geoinformatics are massively or marginally used. The quantitative results are presented, supported by examples and descriptions. Finally, cues and critical issues coming from the research are discussed.

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“…Depending on user needs, quality assessment methods are aimed either at assessing the quality of a VGI dataset as a whole, or at punctually selecting or filtering only the VGI items that satisfy some requirements. In (Bordogna et al, 2014b) a schema for classifying VGI projects to predict the quality characteristics of their created VGI is proposed. This schema can provide a guideline for adopting a specific quality assessment approach, more suitable for the given situation.…”

Section: Related Workmentioning

confidence: 99%

A User-Driven Selection of Vgi Based on Minimum Acceptable Quality Levels

Bordogna

Carrara

Criscuolo

et al. 2015

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Despite Volunteered Geographic Information (VGI) activities are now extremely helpful in a number of scientific applications, researchers and decision makers oppose some resistance to the usage of volunteered contributions, due to quality issues. Several methods and workflows have been proposed to face quality issues in different VGI projects, usually built ad-hoc for specific datasets, thus resulting neither extensible nor transferable. In order to overcome this weakness, the authors propose to perform an user-driven assessment on VGI items in order to filter only those that satisfy minimally acceptable quality levels defined according to their specific quality requirements and project goals. In the present work the users, i.e., information consumers, are seen as decision makers and are allowed to set the minimum acceptable quality levels Thus the approach proposes a user driven assessment of the fitness for use of VGI items. The paper first briefly presents a view on VGI components and suitable quality indices, then it describes a logic architecture for managing them and for enabling a querying mechanism to the datasets. The approach is finally exemplified with a case study simulation.

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On predicting and improving the quality of Volunteer Geographic Information projects

Cited by 42 publications

References 23 publications

Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information

Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information

CS Projects Involving Geoinformatics: A Survey of Implementation Approaches

A User-Driven Selection of Vgi Based on Minimum Acceptable Quality Levels

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