Abstract

Problem, research strategy, and findings

Big data promises new insights for planning but threatens to exclude community expertise from knowledge creation and decision-making processes. Participatory methods are needed to ensure that big data is marshaled to address problems of importance to communities, that hypotheses and interpretations are shaped by evidence from lived experience, and that results are ultimately useful to residents. In this study we used a participatory action research (PAR) framework to engage Boston (MA)–area residents in leveraging a longitudinal consumer credit database to understand shared planning challenges. We describe how residents, community organizations, and academic researchers collaborated to co-design an interactive map of residential moves across Massachusetts. The resulting estimates were largely consistent with residents’ understandings of local moving patterns, providing a case of big data analysis confirming, and further specifying, phenomena identified through centering lived experience. Collaborative data analysis also generated new insights; for example, showing misalignment between regional planning boundaries and low-credit movers’ moving patterns. This work shows how sustained PAR partnerships can combine the strengths of community expertise and big data analyses to inform planning.

Takeaway for practice

PAR with big data is feasible, combines the power of lived experience and large-scale quantitative analysis, and can mitigate the risks of exclusion that threaten emerging uses of big data.

中文翻译：

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移动映射器

摘要

问题、研究策略和发现

大数据为规划提供了新的见解，但有可能将社区专业知识排除在知识创造和决策过程之外。需要采用参与式方法来确保整合大数据以解决对社区重要的问题，确保假设和解释由来自生活经验的证据形成，并且结果最终对居民有用。在这项研究中，我们使用参与式行动研究 (PAR) 框架让波士顿 (MA) 地区的居民利用纵向消费者信用数据库了解共同的规划挑战。我们描述了居民、社区组织和学术研究人员如何合作共同设计马萨诸塞州住宅移动的交互式地图。由此产生的估计与居民对当地移动模式的理解基本一致，提供了一个大数据分析的案例，证实并进一步说明了通过以生活经验为中心识别的现象。协作数据分析也产生了新的见解；例如，显示区域规划边界与低信贷移动者的移动模式之间的错位。这项工作展示了持续的 PAR 合作伙伴关系如何结合社区专业知识和大数据分析的优势来为规划提供信息。

练习外卖

PAR 与大数据是可行的，结合了生活经验和大规模定量分析的力量，可以减轻威胁大数据新兴用途的排斥风险。