Next Article in Journal
An Integrated Approach for Monitoring and Information Management of the Guanling Landslide (China)
Next Article in Special Issue
Assessing Crowdsourced POI Quality: Combining Methods Based on Reference Data, History, and Spatial Relations
Previous Article in Journal
A Web-Based Visual and Analytical Geographical Information System for Oil and Gas Data
Previous Article in Special Issue
Crowdsourcing User-Generated Mobile Sensor Weather Data for Densifying Static Geosensor Networks
Article Menu
Issue 3 (March) cover image

Export Article

Open AccessArticle
ISPRS Int. J. Geo-Inf. 2017, 6(3), 78; doi:10.3390/ijgi6030078

On Data Quality Assurance and Conflation Entanglement in Crowdsourcing for Environmental Studies

1
Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2RD, UK
2
Earth Observation Group, Aberystwyth University Penglais, Aberystwyth SY23 3FL, UK
3
College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, UK
4
EDINA, University of Edinburgh, Edinburgh EH8 9YL, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Alexander Zipf, Linda See, David Jonietz, Vyron Antoniou and Wolfgang Kainz
Received: 30 November 2016 / Revised: 6 March 2017 / Accepted: 8 March 2017 / Published: 11 March 2017
(This article belongs to the Special Issue Volunteered Geographic Information)
View Full-Text   |   Download PDF [1397 KB, uploaded 11 March 2017]   |  

Abstract

Volunteer geographical information (VGI), either in the context of citizen science or the mining of social media, has proven to be useful in various domains including natural hazards, health status, disease epidemics, and biological monitoring. Nonetheless, the variable or unknown data quality due to crowdsourcing settings are still an obstacle for fully integrating these data sources in environmental studies and potentially in policy making. The data curation process, in which a quality assurance (QA) is needed, is often driven by the direct usability of the data collected within a data conflation process or data fusion (DCDF), combining the crowdsourced data into one view, using potentially other data sources as well. Looking at current practices in VGI data quality and using two examples, namely land cover validation and inundation extent estimation, this paper discusses the close links between QA and DCDF. It aims to help in deciding whether a disentanglement can be possible, whether beneficial or not, in understanding the data curation process with respect to its methodology for future usage of crowdsourced data. Analysing situations throughout the data curation process where and when entanglement between QA and DCDF occur, the paper explores the various facets of VGI data capture, as well as data quality assessment and purposes. Far from rejecting the usability ISO quality criterion, the paper advocates for a decoupling of the QA process and the DCDF step as much as possible while still integrating them within an approach analogous to a Bayesian paradigm. View Full-Text
Keywords: data curation; data quality; ISO standard; data fusion; data conflation; citizen science; crowdsourcing data curation; data quality; ISO standard; data fusion; data conflation; citizen science; crowdsourcing
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Leibovici, D.G.; Rosser, J.F.; Hodges, C.; Evans, B.; Jackson, M.J.; Higgins, C.I. On Data Quality Assurance and Conflation Entanglement in Crowdsourcing for Environmental Studies. ISPRS Int. J. Geo-Inf. 2017, 6, 78.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top