Great Britain Transport, Employment Access Datasets for small-area Urban Area Analytics

This paper provides a brief description of four new forms of key datasets relevant to urban analytics studies namely: Transport, Housing and Employment Accessibility and Education, covering Great Britain, developed by the Urban Big Data Centre (UBDC). Full details of the research related to this paper are contained in “Spatial urban data system: A cloud-enabled big data infrastructure for social and economic urban analytics”[1]The transport Dataset contains public transport availability (PTA) indicators at both the stop/station and small-area levels (lower layer super output area (LSOA) and middle layer super output area (MSOA)). The employment dataset provides information on the number of people with access to employment within specific distances from each output area. The housing datasets contains quarterly house rent and sales prices aggregated at output area level (MSOA). The education data contains secondary school (Greater Glasgow Area, Scotland) and Higher Education (Great Britain) student-level data. In addition to all educational outcomes at school stages S4-S6, the secondary school pupil data consists of age, gender, nationality and ethnic background, level of English, attendance, post-school destinations, and receipt of Gaelic education. This is augmented by individual schools’ data consisting of staffing levels, proportions of pupils’ speaking particular languages at home, religious denomination, distance travelled by students from home, and accessibility to greenspace from both the home and school neighbourhoods. The higher education (HE) dataset consists of home and term-time locations (at postcode sector level), subject studied, level and mode of study of courses, level and classification of qualification, and post-HE destination. The theoretical background for measuring the datasets at small area levels is also presented in this paper. Additionally, a variety of raw data used to produce some of the datasets (e.g. PTA) is also introduced to enable interested readers to reproduce them.本文简要介绍了由城市大数据中心（Urban Big Data Centre，UBDC）针对英国全境开发的、与城市分析研究相关的四类核心新型数据集，分别为交通、住房、就业可达性与教育数据集。本文相关研究的完整细节载于论文《空间城市数据系统：面向社会与经济城市分析的云赋能大数据基础设施》[1]。 交通数据集包含站点级与小区域级（低层超级输出区（Lower Layer Super Output Area，LSOA）及中层超级输出区（Middle Layer Super Output Area，MSOA））的公共交通可达性（Public Transport Availability，PTA）指标。就业数据集提供了各输出区周边特定距离范围内可获得就业岗位的人口数量相关信息。住房数据集包含以输出区（MSOA）为聚合单元的季度房屋租金与销售价格数据。教育数据集涵盖苏格兰大格拉斯哥地区的中等教育层面以及英国全境的高等教育（Higher Education，HE）层面的学生个体数据。 中学阶段学生数据除包含S4至S6学段的全部教育成果外，还涵盖学生的年龄、性别、国籍与族裔背景、英语水平、出勤情况、毕业后去向以及盖尔语教育参与情况。该数据集还补充了各中学的相关数据，包括教职工人数、学生家庭使用特定语言的比例、宗教教派、学生上下学通勤距离，以及学生家庭与学校周边区域的绿地可达性情况。高等教育（HE）数据集包含学生的家庭住址与学期就读地址（以邮编分区为单元）、所学专业、课程的学习层次与学习模式、学历层次与学位等级，以及毕业后的去向信息。 本文还阐述了以小区域为单元构建数据集的理论背景。此外，本文还介绍了用于生成部分数据集（如公共交通可达性指标PTA）的各类原始数据，以供感兴趣的读者复现相关研究结果。