Utilizing fuzzy set theory to assure the quality of volunteered geographic information
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This paper presents a fuzzy system to assure the quality of volunteered geographic information (VGI) collected for the purposes of species surveillances. The system uses trust as a proxy of quality. It defines the trust using both the provenance of user expertise and the fitness of geographic context and quantifies it using fuzzy set theory. The system was applied to a specific scenario—VGI-based crop pest surveillance—to demonstrate its usefulness in handling VGI quality. A case study was conducted in Jiangxi province of China, where location-based rice pest surveillance reports generated by the local farmers were collected. A field pest survey was conducted by the local pest management experts to verify the farmer-generated reports, and the survey results were used as ground truth data. The quality of the farmer-generated reports were also assessed through the fuzzy system and compared to the pest survey results. It was observed that the degree to which these two sets of results agreed to each other was satisfactory.
KeywordsVolunteered geographic information Data quality Fuzzy system Species surveillance
This research has been supported by National University of Singapore (NUS); and Singapore National Research Foundation under its Inter-national Research Centre @ Singapore Funding Initiative and administered by the IDM Programme Office through the Centre of Social Media Innovations for Communities (COSMIC).
Compliance with ethical standards
Conflict of interest
We declare that there are no real or perceived conflicts of interest involved in the submission and/or publication of this manuscript.
This research involved human participants (farmers) as volunteers contributing location-based crop pest surveillance reports for evaluating the performance of the proposed approach of VGI quality assurance. Verbal consents of participation were sought from the participants.
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