TY - JOUR
T1 - Trust as a proxy indicator for intrinsic quality of Volunteered Geographic Information in biodiversity monitoring programs
AU - Vahidi, Hossein
AU - Klinkenberg, Brian
AU - Yan, Wanglin
N1 - Funding Information:
The authors would like to thank Professor Dr. Michael F. Goodchild of University of California, Santa Barbara for his valuable comments and suggestions to improve the quality of this article.
Publisher Copyright:
© 2017 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2018/7/4
Y1 - 2018/7/4
N2 - In this article, we present a fuzzy model for intrinsic quality assessment of Volunteered Geographic Information (VGI) on species occurrences obtained by Citizen Science (CS) biodiversity monitoring programs. The proposed VGI quality assurance approach evaluates the thematic and positional quality of the crowdsourced biodiversity observation in terms of the trustworthiness of the observation by combining three indicators of consistency with habitat, consistency with surroundings, and reputation of contributor, that characterize the geographical and social aspects of trust in VGI. To evaluate the performance and usability of the proposed approach for evaluating the trustworthiness of crowdsourced observations and detecting thematic and positional errors in crowdsourced observations, the developed approach was applied to the crowdsourced observations on Acer macrophyllum collected through the CS biodiversity monitoring projects of E-Flora BC and iNaturalist. The result of a conformity test at the optimal acceptance threshold (sensitivity = 0.99, specificity = 0.8, and Cohen’s kappa = 0.79), the achieved area under the curve (AUC) value (AUC = 0.98), and the results of the complementary investigation on the predictions of the proposed model indicated that the proposed fuzzy trust model exhibited promising predictive performance and was able to flag the majority of attribute and positional errors in the crowdsourced biodiversity observations.
AB - In this article, we present a fuzzy model for intrinsic quality assessment of Volunteered Geographic Information (VGI) on species occurrences obtained by Citizen Science (CS) biodiversity monitoring programs. The proposed VGI quality assurance approach evaluates the thematic and positional quality of the crowdsourced biodiversity observation in terms of the trustworthiness of the observation by combining three indicators of consistency with habitat, consistency with surroundings, and reputation of contributor, that characterize the geographical and social aspects of trust in VGI. To evaluate the performance and usability of the proposed approach for evaluating the trustworthiness of crowdsourced observations and detecting thematic and positional errors in crowdsourced observations, the developed approach was applied to the crowdsourced observations on Acer macrophyllum collected through the CS biodiversity monitoring projects of E-Flora BC and iNaturalist. The result of a conformity test at the optimal acceptance threshold (sensitivity = 0.99, specificity = 0.8, and Cohen’s kappa = 0.79), the achieved area under the curve (AUC) value (AUC = 0.98), and the results of the complementary investigation on the predictions of the proposed model indicated that the proposed fuzzy trust model exhibited promising predictive performance and was able to flag the majority of attribute and positional errors in the crowdsourced biodiversity observations.
KW - Volunteered Geographic Information
KW - biodiversity monitoring
KW - citizen science
KW - crowdsourcing
KW - intrinsic data quality indicator
KW - trust
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U2 - 10.1080/15481603.2017.1413794
DO - 10.1080/15481603.2017.1413794
M3 - Article
AN - SCOPUS:85038104251
SN - 1548-1603
VL - 55
SP - 502
EP - 538
JO - GIScience and Remote Sensing
JF - GIScience and Remote Sensing
IS - 4
ER -