EAGER: Data Science for Election Verification

选举官员需要循证的、科学有效的工具来例行评估选举制度的质量，包括技术和人为因素。无论是由选举管理人员还是由选举各方发起，选举调查都是昂贵的，必须优先考虑才能最有效。该项目计划为选举官员和其他人提供优先调查的工具。预期的结果是保护选举的机制更加稳健，这可以让美国人对选举结果更有信心。这项研究将有助于改变数据科学用于保护选举的方式。社会还没有一个可持续的系统数据科学生态系统，以告知选举管理人员，政党和候选人如何优先考虑其有限的调查资源。选举的特殊性可能需要开发预测分析的新技术。目标是预测元素集合的行为，而不是单个元素的行为。分析必须在候选人、竞选活动和文化趋势的特殊影响所造成的局部噪音和整体趋势的存在下进行。该项目的目标是加强美国选举的实际和感知完整性。选举制度是重要的基础设施。保护选举是国家安全的一部分。这将通过提高我们发现和纠正错误选举结果的能力，提高美国选举基础设施的弹性。此外，由于选举安全问题的高度可见性，这项工作将促进公众对数据科学的参与。这项研究将收集全国各地选举机构使用的技术数据。这些数据将在www.VerifiedVoting.org/verifier上公开。该研究还将创建原型分析和可视化工具，并将公开共享。研究将从对少数管辖区的真实的选举产生明显影响的相对简单的分析进展到涉及更广泛数据的分析，包括人口普查和选举技术数据，该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响力进行评估来支持。审查标准。

Election officials need evidence-based, scientifically valid tools to routinely assess the quality of election systems, including technical and human factors. Whether initiated by the election administrators or by the parties to an election, election investigation is expensive and must be well prioritized to be most effective. The project plans to provide tools for prioritizing investigations for election officials and others. The expected outcome is increased robustness of the mechanisms protecting elections that can give Americans more justified confidence in election results.The research will help transform the way data science is used to protect elections. Society does not yet have a sustainable ecosystem of systematic data science to inform decisions by election administrators, political parties and candidates about how to prioritize their limited investigation resources. The peculiarities of elections may require development of new techniques in predictive analytics. The goal is to predict the behavior of a collection of elements, not the behavior of single elements. The analysis must be done in the presence of local noise and overall trends created by idiosyncratic effects of candidates, campaigns and cultural trends.The project's goal is to bolster the actual and perceived integrity of American elections. Election systems are critical infrastructure. Protecting elections is part of national security. This will increase the resilience of US election infrastructure by improving our ability to detect and correct erroneous election results. In addition, because of the high visibility of election security issues, the work will promote public engagement with data science.The research will collect data on the technology fielded by election agencies across the country. This data will be publicly available at www.VerifiedVoting.org/verifier. The research will also create prototype analysis and visualization tools that will be shared publicly. The research will progress from relatively simple analyses that have had a demonstrable impact on real elections in a few jurisdictions to analyses involving a wider variety of data, including census and election technology data, and more sophisticated predictive analytics and machine learning algorithms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.