SocioMap: A tool for exploring, translating, and merging data across complex sociopolitical categories
SocioMap: A tool for exploring, translating, and merging data across complex sociopolitical categories
批准号:
2051369
负责人:
Daniel Hruschka
金额:
$15.55万
依托单位:
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
项目状态:
已结题
起止时间:
2021-06-01 至 2024-05-31
中文摘要
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、移徙、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上合并多个数据集(例如,种族、语言、宗教或省份)。然而,不同的数据集通常使用不同的变量名称、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一个巨大的瓶颈。 该项目将建立一个名为SocioMap的新数据分析平台,通过提供工具来翻译大量不断增长的国际社会科学数据集,并从不同的现有数据集构建新的数据集,以帮助克服这一瓶颈,这些数据集存储不同的种族,宗教,语言和行政边界,SocioMap将是一套用户友好的工具,有助于在多个外部数据集之间转换社会政治类别和分类方案。这个项目将集中在四种类别-种族,语言,宗教和行政边界-这是社会科学研究中常用的。 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,这些类别涉及数十个共同标准和数百个世界各地的人口调查和普查。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)从新数据集,标准和已发表的研究中翻译和共享类别,(3)合并数据集的新组合以满足研究人员的自定义研究需求,以及(4)记录分析工作流程的关键方面,这些方面往往未被报告,并在这样做的过程中,使分析更具可重复性。SocioMap通过提供工具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,文化和人口统计数据联系起来,补充了现有的观测数据集。 SocioMap的能力将刺激新的跨学科研究,鼓励对公共资助的数据进行新的分析,并重新评估过去发现的稳健性和可重复性。 该奖项还将为未来与其他类型的实体(如政党、非政府组织、行业和职业分类以及公司)的合作以及在更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NSF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。
英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
HNDS-I: CatMapper: User-friendly tools for integrating data by complex, dynamic categories
-
批准号:2318505
-
项目类别:Standard Grant
-
资助金额:$54.99万
-
财政年份:2023
-
负责人:Daniel Hruschka
-
依托单位:
RR: Building a Robust Foundation for Measuring Material Wealth in Low- and Middle-Income Settings
-
批准号:1658766
-
项目类别:Standard Grant
-
资助金额:$21.46万
-
财政年份:2017
-
负责人:Daniel Hruschka
-
依托单位:
Workshop: Enhancing robust and generalizable experimental behavioral science
-
批准号:1623555
-
项目类别:Standard Grant
-
资助金额:$2.16万
-
财政年份:2016
-
负责人:Daniel Hruschka
-
依托单位:
CAREER: Social Closeness, Helping, and Neglect: Examining the Roots of Favoritism in Rural Bangladesh
-
批准号:1150813
-
项目类别:Continuing Grant
-
资助金额:$50.65万
-
财政年份:2012
-
负责人:Daniel Hruschka
-
依托单位:
海外基金