HCC: Small: Human-Centered Computing to Support Citizen Data Science on Gender-based Violence

这项研究旨在更好地理解公民数据做法，即哪些数据与严重的社会问题有关对公民更重要，以及公民对开放数据实际做了什么。它侧重于关于基于性别的暴力的公民数据，特别是关于基于性别的原因杀害妇女和女孩的数据。尽管人们对公开数据进行了大量研究，并对其对民主的好处进行了猜测，但实证性的工作相对较少。众所周知，关于性别暴力和杀害女性的官方数据往往不完整、难以获取、不经常更新，而且报告不足。公民团体已经填补了这些按性别划分的数据差距。这项研究项目旨在经验性地研究从事公民数据科学的团体关于杀害女性的信息实践，并为以人类为中心的计算如何更好地支持这项工作开发设计含义。通过将即席公民实践系统化为经验模型，培养公民以人为本的计算机设计思想，这项工作将推动公民数据科学在女性杀戮主题上的实践，并支持公共意识、政策和公民社会-公共部门关于性别暴力公民数据的合作。本研究将对人机交互、关键数据研究、妇女和性别研究以及社会学领域的学术文献做出四项贡献。(1)经验性贡献：该项目首先旨在促进对公民数据科学做法的经验性理解，这些做法关于杀害女性和基于性别的杀戮一直是很少研究的主题。这将为数字工具和研究提供经验基础，这些工具和研究可以更好地支持公民关于基于性别的暴力的数据科学，并可能在未来导致政府和民间社会围绕杀害女性的数据加强合作。(2)方法论贡献：虽然对公民数据做法的研究通常侧重于案例研究，但这项研究将对这些做法进行更广泛的跨国分析，涉及公民有大量精力和活动的特定主题领域。(3)设计贡献：通过以平等和参与性的方式与群体本身合作，它将为以人为中心的计算贡献高层次的设计影响，以支持关于基于性别的暴力的公民数据科学，并将此类群体的声音和经验集中在设计过程中。(4)结论的概括性：对本研究中探索的基本概念和研究方法的评估将为基于性别的暴力领域以外以公平为导向的公民数据科学提供基础。这一奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This study seeks to better understand citizen data practices, namely, which data are related to serious social problems are more important to citizens and what citizens actually do with open data. It focuses on citizen data about gender-based violence, and specifically data about the killing of women and girls for reasons based on their gender. While there has been a great deal of research on open data, and speculation about its benefits to democracy, there has been comparatively less empirical work. It is well-established that official data on gender violence and feminicide are often incomplete, difficult to access, infrequently updated, and underreported. Citizen groups have stepped into these gendered data gaps. This research project aims to empirically study the informatic practices of groups that undertake citizen data science about feminicide as well as develop design implications for how human-centered computing may better support this work. By systematizing ad-hoc citizen practices into an empirical model and cultivating citizens' own human-centered computing design ideas, this work will advance the practice of citizen data science on the topic of feminicide as well as support public awareness, policy and civil society-public sector collaboration on civic data about gender-based violence.This research will make four contributions to the scholarly literature in the fields of human-computer interaction, critical data studies, women's and gender studies, and sociology. (1) Empirical contribution: The project aims first of all to advance empirical understanding of citizen data science practices about feminicide and gender-based killing which have been the subject of little research. This will provide the empirical groundwork for digital tools and research that can better support citizen data science about gender-based violence, and could potentially lead to increased government-civil society cooperation around feminicide data in the future. (2) Methodological contribution: While research on citizen data practices typically focuses on case studies, this research will undertake a broader and transnational analysis of these practices across a specific topical domain where there is significant citizen energy and activity. (3) Design contribution: By working in an equitable and participatory way with groups themselves, it will contribute high-level design implications for human-centered computing to support citizen data science about gender-based violence, and center the voices and experiences of such groups in the design process. (4) Generalizability of findings: An assessment of fundamental concepts and research methods explored in this research will provide groundwork for equity-oriented citizen data science beyond the domain of gender-based violence.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.