Census 2022: Transforming Small Area Socio-Economic Indicators through 'Big Data'
Census 2022: Transforming Small Area Socio-Economic Indicators through 'Big Data'
批准号:
ES/L00318X/1
负责人:
Ben Anderson
金额:
$25.2万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2013
资助国家:
英国
项目状态:
已结题
起止时间:
2013 至 --
中文摘要
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英文摘要
The potentially imminent demise of the decennial UK Census presents social, policy and commercial researchers with both a challenge and an opportunity. The challenge is to transform 'census-taking' by finding robust alternative methods for creating traditional small area socio-economic indicators over time ('census-like' indicators). The opportunity is to transform the very nature of the socio-economic indicators themselves using new analytic methods applied to new geo-coded datasets and to radically accelerate the temporal cycle from decennial to annual or sub-annual production ('census-plus' indicators). If we are no longer to be restricted to what can be asked in a Census, then what kinds of social indicators might we want or be able to produce, how regularly and what forms of novel social, policy and commercial analysis might this then underpin? This project will address these questions using existing large-scale geo-coded transactional datasets held at the University of Southampton. These include household level energy monitoring, historical telephone call records and other forms of data and the project will build on recent exploratory work to develop and validate methods for estimating small area 'Census-like' and 'Census-plus' indicators. The project will test the utility of a range of analytic techniques for deriving traditional and novel small area socio-economic indicators including relatively simple ratios and distribution measures as well as more experimental temporal sequence and profile analysis.As far as we are aware no such analysis has been attempted and yet, if successful the approach has the potential to radically transform the nature and temporality of small area indicators. Aggregated data from a range of transactional sources might be able to provide replacements for census-like small area tables on at least an annual basis thus providing a resource not only for temporally fine-grained small area social-economic trend observation but also fine grained local intervention impact assessment. In addition the sources may also have the potential to provide totally new but similarly temporally fine-grained small area socio-economic indicators that can provide radically new ways to investigate local and regional socio-economic trends. Potential examples include the estimation of social-interaction based indicators from social communication traces and social-sustainability indicators from energy consumption/production measurements.The project will be run as a series of co-ordinated sub-projects testing different techniques on different datasets and all results will be published through a regularly updated project website as well as through the usual academic channels of working papers, presentations and journal articles. In addition we will engage closely with potential research users, in particular the ONS' Beyond 2011 team who may be able to directly exploit the research in their studies of future census-taking options.
期刊论文(8)
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Extracting value from near real time domestic energy consumption data in a post-census era
在后人口普查时代从近乎实时的国内能源消耗数据中提取价值
DOI:
--
发表时间:
2014
期刊:
RGS/IBG Annual Conference 2014
影响因子:
--
作者:
[Newing, A]
通讯作者:
Newing, A
DOI:
10.1016/j.compenvurbsys.2016.06.003
发表时间:
2017-05-01
期刊:
COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
影响因子:
6.8
作者:
[Anderson, Ben, Lin, Sharon, James, Patrick]
通讯作者:
James, Patrick
Census2022: Extracting value from domestic consumption data in a postcensus era
2022 年人口普查:从后人口普查时代的国内消费数据中提取价值
DOI:
--
发表时间:
2014
期刊:
BEHAVE Conference 2014, Oxford
影响因子:
--
作者:
[Anderson, B]
通讯作者:
Anderson, B
DOI:
10.1002/psp.1972
发表时间:
2016-11-01
期刊:
POPULATION SPACE AND PLACE
影响因子:
2.4
作者:
[Newing, Andy, Anderson, Ben, James, Patrick]
通讯作者:
James, Patrick
Census2022: Using big data from electricity smart metering to support geodemographics and small area profiling
2022 年人口普查:利用电力智能计量的大数据支持地理人口统计和小区域分析
DOI:
--
发表时间:
2014
期刊:
British and Irish Section, Aberystwyth, 19th-21st August 2014.
影响因子:
--
作者:
[Newing, A]
通讯作者:
Newing, A
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