SocioMap: A tool for exploring, translating, and merging data across complex sociopolitical categories

SocioMap：用于探索、翻译和合并复杂社会政治类别数据的工具

• 批准号: 2051369
• 负责人: Daniel Hruschka
• 金额: $ 15.55万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2051369&HistoricalAwards=false
• 关键词: SocioMap; tool; exploring; translating; merging

Social scientists are increasingly using data from diverse, worldwide sources to understand the causes and consequences of social stratification, migration, economic development, cultural diversity and violent conflict. This work frequently requires merging multiple datasets over fine-grained sociopolitical categories (e.g., ethnicities, languages, religions, or provinces). However, different datasets often encode corresponding sociopolitical categories with different variable names, at different scales, and different points in. These different encodings must be translated across datasets before merging, thereby creating a substantial bottleneck to interdisciplinary, comparative social science. This project will build a new data analysis platform called SocioMap that will help overcome this bottleneck by providing tools for translating across a large and growing body of international social science datasets and for building new datasets from diverse existing datasets storing ethnic, religious, linguistic, and administrative boundaries in disparate, and non-compatible formats.SocioMap will be a user-friendly set of tools to help translate sociopolitical categories and classification schemes across multiple, external datasets. This project will focus on four kinds of categories — ethnicities, languages, religions, and administrative boundaries — that are commonly used in social science research. The beta version of SocioMap will be injected with a critical mass of these categories and translations between these categories across dozens of common standards and hundreds of demographic surveys and censuses worldwide. Furthermore, SocioMap is designed to grow by permitting registered users to add new categories and translations for re-use in future projects. SocioMap’s tools will help users: (1) explore contextual information about specific sociopolitical categories, (2) translate and share categories from new datasets, standards, and published studies, (3) merge novel combinations of datasets for researchers’ custom research needs, and (4) document key aspects of the analytical workflow that often go unreported and, in so doing, make analyses more reproducible. SocioMap complements existing observational datasets by providing tools for linking these datasets with social, cultural, and demographic data from a diverse and growing body of new datasets. SocioMap’s capabilities will spur new interdisciplinary research, encourage new analyses of publicly funded data and re-assessments of the robustness and reproducibility of past findings. It will also create a foundation for future work with other kinds of entities (e.g. political parties, non-governmental organizations, industry and occupation classifications, and firms) and for reconciling sociopolitical entities over longer historical periods.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.

社会科学家越来越多地使用来自世界各地的各种数据来了解社会分层、移民、经济发展、文化多样性和暴力冲突的原因和后果。这项工作经常需要在细粒度的社会政治类别（例如，种族，语言，宗教或省份）上合并多个数据集。然而，不同的数据集通常用不同的变量名称、不同的尺度和不同的点来编码相应的社会政治类别。这些不同的编码必须在合并之前跨数据集进行翻译，从而为跨学科的比较社会科学创造了实质性的瓶颈。该项目将建立一个名为SocioMap的新数据分析平台，该平台将通过提供工具来翻译庞大且不断增长的国际社会科学数据集，并从以不同且不兼容的格式存储种族、宗教、语言和行政边界的各种现有数据集构建新数据集，从而帮助克服这一瓶颈。SocioMap将是一套用户友好的工具，帮助翻译跨多个外部数据集的社会政治类别和分类方案。本项目将重点关注社会科学研究中常用的四种类别——种族、语言、宗教和行政边界。SocioMap的测试版将注入大量的这些类别，以及这些类别之间的翻译，这些分类跨越数十个共同标准和数百个全球人口调查和人口普查。此外，SocioMap的设计允许注册用户添加新的类别和翻译，以便在未来的项目中重复使用。SocioMap的工具将帮助用户：(1)探索有关特定社会政治类别的上下文信息；(2)翻译和分享来自新数据集、标准和已发表研究的类别；(3)合并数据集的新组合，以满足研究人员的定制研究需求；(4)记录分析工作流程中经常未报告的关键方面，并通过这样做，使分析更具可重复性。SocioMap补充了现有的观测数据集，提供了将这些数据集与来自多样化和不断增长的新数据集的社会、文化和人口数据联系起来的工具。SocioMap的功能将刺激新的跨学科研究，鼓励对公共资助数据进行新的分析，并重新评估过去发现的稳健性和可重复性。它还将为今后与其他类型实体（如政党、非政府组织、工业和职业分类以及公司）的合作以及在较长的历史时期内协调社会政治实体奠定基础。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。