Investigating how the public sector adopts technologies to process and analyze very large datasets is crucial for understanding governance in the digital age. The authors of this article examine a large government agency, the United States Border Patrol (USBP), an organization that is in the early phases of building big data capabilities. They argue the wide-scale adoption of big data analytics will require trial-and-error processes coordinated by organizational leadership in partnership with front-line employees who make the technology relevant to their needs in the field. Absent engagement from both levels, organizations like USBP that face significant barriers to adoption (e.g., limited data science expertise) will struggle to leverage data at scale. The authors also extend the literature on big data in the public sector and provide a rich description of how factors, such as organizational leadership and resources, impact the innovation process.

中文翻译：

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将大数据应用于政府：以美国边境巡逻队为例

调查公共部门如何采用技术来处理和分析超大型数据集对于理解数字时代的治理至关重要。本文作者考察了一个大型政府机构，即美国边境巡逻队 (USBP)，该组织处于构建大数据能力的早期阶段。他们认为，大数据分析的大规模采用将需要组织领导层与一线员工合作协调试错过程，这些员工使技术与他们在该领域的需求相关。如果没有两个层面的参与，像 USBP 这样面临重大采用障碍（例如，有限的数据科学专业知识）的组织将难以大规模利用数据。