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Publication Detail
Ensuring VGI Credibility in Urban-Community Data Generation: A Methodological Research Design
Abstract
In this paper we outline the methodological development of current research into urban community formations based on combinations of qualitative (volunteered) and quantitative (spatial analytical and geo-statistical) data. We outline a research design that addresses problems of data quality relating to credibility in volunteered geographic information (VGI) intended for Web-enabled participatory planning. Here we have drawn on a dual notion of credibility in VGI data, and propose a methodological workflow to address its criteria. We propose a ‘super-positional’ model of urban community formations, and report on the combination of quantitative and participatory methods employed to underpin its integration. The objective of this methodological phase of study is to enhance confidence in the quality of data for Web-enabled participatory planning. Our participatory method has been supported by rigorous quantification of area characteristics, including participant communities’ demographic and socio-economic contexts. This participatory method provided participants with a ready and accessible format for observing and mark-making, which allowed the investigators to iterate rapidly a system design based on participants’ responses to the workshop tasks. Participatory workshops have involved secondary school-age children in socio-economically contrasting areas of Liverpool (Merseyside, UK), which offers a test-bed for comparing communities’ formations in comparative contexts, while bringing an under-represented section of the population into a planning domain, whose experience may stem from public and non-motorised transport modalities. Data has been gathered through one-day participatory workshops, featuring questionnaire surveys, local site analysis, perception mapping and brief, textual descriptions. This innovative approach will support Web-based participation among stakeholding planners, who may benefit from well-structured, community-volunteered, geo-located definitions of local spaces.
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