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Ensuring VGI Credibility in Urban-Community Data Generation: A Methodological Research Design

机译:在城市社区数据生成中确保VGI可信度:一种方法研究设计

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摘要

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.
机译:在本文中,我们概述了基于定性(自愿)数据和定量(空间分析和地统计)数据相结合的当前城市社区形成研究的方法论发展。我们概述了一项研究设计,该研究设计旨在解决基于Web的参与式计划的自愿性地理信息(VGI)中与信誉有关的数据质量问题。在这里,我们在VGI数据中采用了可信度的双重概念,并提出了一种解决其标准的方法工作流程。我们提出了一种城市社区形成的“超位置”模型,并报告了用于支持其整合的定量和参与式方法的结合。该研究方法阶段的目的是增强对基于Web的参与式计划的数据质量的信心。我们的参与式方法得到了区域特征的严格量化的支持,其中包括参与者社区的人口统计学和社会经济背景。这种参与式方法为参与者提供了易于使用的观察和标记格式,这使研究人员可以根据参与者对讲习班任务的反应快速迭代系统设计。参与性讲习班在利物浦(英国默西塞德郡)的社会经济差异地区参加了中学适龄儿童的学习,这为在比较情况下比较社区的形成提供了一个试验台,同时使人数不足的部分人口融入了社会。规划领域,其经验可能来自公共和非机动交通方式。数据是通过为期一天的参与式研讨会收集的,其中包括问卷调查,本地站点分析,感知映射以及简短的文本描述。这种创新的方法将支持利益相关者计划者基于Web的参与,他们可能会受益于结构合理,社区志愿服务的地理位置对本地空间的定义。

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