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Smart Data Analytics for Business and Local Government

Smart Data Analytics for Business and Local Government
企业和地方政府的智能数据分析
批准号:
ES/L011859/1
负责人:
Maria Fasli
金额:
$662.36万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2014
资助国家:
英国
项目状态:
已结题
起止时间:
2014 至 --

项目摘要

项目成果

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中文摘要
翻译
我们生活在一个大数据时代,信息技术和通信技术的快速发展提供了前所未有的数据量和新的数据形式。大数据现在是我们日常生活中不可或缺的一部分,通常由地方政府和企业生产。在这些情况下,数据生产只是地方政府或企业参与的活动的副产品:大多数情况下,这些信息是为了特定目的而收集的,但这些数据集除了最初的设计目的之外,很少被使用。挑战是我们如何更好地利用这些类型的信息来提高我们的生活质量和促进经济增长。如果结合在一起,这些数据集可以提供有价值的信息和洞察,了解企业和地方当局如何运作,如何改进服务,或者企业在运营中变得更加成功和高效。大数据可以为地方当局和企业提供额外的信息,帮助他们制定更好的政策,改善业务运营。迄今为止,用于社会科学系统研究的这类数据很少。新的商业和地方政府智能数据分析(SDA)研究中心的目的是利用这一爆炸性的信息进行社会科学研究,以回答影响我们所有人生活的问题。例如,在地方当局紧缩开支和勒紧裤腰带的时代,他们如何才能最好地利用有限的资源向居民提供最高质量的服务,包括在卫生和社会保健提供、教育、减少犯罪、住房和交通方面?通过利用地方当局为其行政目的收集的数据来源,我们可以开始解决其中一些问题,并提出相关和及时的政策建议。我们已经与肯特郡、埃塞克斯郡和诺福克郡的三个地方议会合作,他们热衷于与学术研究人员合作,从他们掌握的信息中学习,以改善他们的服务提供,但目前还没有充分利用。我们还与希望了解我们如何促进和支持经济增长,特别是中小企业和初创企业的经济增长的企业建立了伙伴关系。这些企业面临的障碍是什么?大数据如何帮助我们了解克服这些障碍的最佳方法?美国农业部将在埃塞克斯大学建立一个安全的数据设施,在那里存储和匹配来自各种来源的大数据,以产生对地方当局和企业都有用的新信息。与此同时,该设施将为研究人员、地方当局和企业提供访问大数据的途径,以及在使用这些数据方面的专业知识和支持。显然有许多数据隐私和保密问题需要考虑,中心将制定处理、匿名和链接数据的安全方法,以确保企业和个人的机密性得到维护和尊重。该中心还将就如何最好地分析大数据进行研究,因为用于更标准形式的数据的一些方法可能不适用,例如社会调查。我们有一个创新的实质性研究方案,包括一系列旨在侧重于关键政策问题的研究流:(1)大数据分析的方法进展;(2)地方经济增长;(3)对弱势群体的支持;以及(4)绿色基础设施。中心还将向新的研究人员、企业和地方当局提供培训和支持,并通过利用中心建立的专门知识的专门知识交流活动,与企业和地方当局积极接触。新的中心将是一个令人兴奋的发展,它不仅将促进知识的发展,而且将对我们的生活质量产生积极影响。
英文摘要
We are living in an era of Big data with the rapid technological developments in information technologies and communications providing an unprecedented amount of data and new forms of data. Big data is now an integral part of our daily lives and are routinely produced by local government and business. In these settings, data production is just a by-product of the activities local government or business are involved in: most often, this information is collected for a specific purpose but very little use is made of these data-sets beyond the original purpose they were designed for. The challenge is how we can make better use of these types of information to improve our quality of life and foster economic growth. If combined together, these datasets can provide valuable information and insights into how businesses and local authorities work, the ways in which improvements to services can be made or businesses become more successful and efficient in their operation. Big data can provide local authorities and businesses additional information which can help them to design better policies and improve their business operations. To date, very little data of this type has been available for social scientific research in a systematic way. The aim of the new Smart Data Analytics (SDA) for Business and Local Government research centre is to utilise this explosion of information for social scientific research to answer questions that affect all our lives. For example, in an era of austerity and belt-tightening for local authorities, how can they make best use of limited resources to deliver the highest quality service to residents including across health and social care provision, education, crime reduction, housing and transport? By using data sources collected by local authorities for their administrative purposes we can start to unravel some of these questions and make relevant and timely policy recommendations. We have partnered with three local councils in Kent, Essex and Norfolk who are keen to work with academic researchers to learn from the information they hold to improve their service delivery but at present do not fully utilise. We have also partnered with businesses who wish to understand how we can foster and support economic growth, particularly for small and medium enterprises and start-ups. What are the barriers these businesses face and how can Big data help us understand the best means of overcoming these?The SDA will establish a secure data facility at the University of Essex where Big data from a variety of sources are stored and matched so to produce new information which can be useful to both local authorities and businesses. At the same time, the facility will give researchers, local authorities and businesses a point of access to Big data and expertise and support in using those data. There are clearly many issues of data privacy and confidentiality to be considered and the Centre will develop safe methods of handling, anonymising and linking data to ensure the confidentiality of businesses and individuals is maintained and respected. The Centre will also carry out research into how Big data can best be analysed as some of the methods used for more standard forms of data such as social surveys may not apply. We have an innovative substantive research programme articulated in a set of research streams designed to focus on key policy issues: (i) Methodological advances in Big Data analysis; (ii) Local economic growth, (iii) Support for vulnerable people; and (iv) the Green Infrastructure. The Centre will also provide training and support to new researchers, businesses and local authorities and engage actively with both businesses and local authorities through tailored knowledge exchange activities which will draw on the expertise built in the Centre. The new Centre promises to be an exciting development that will not only advance knowledge but have a positive impact on our quality of life.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
Causal Inference with Correlation Alignment
具有相关性对齐的因果推理
DOI: --
发表时间: 2020
期刊:
影响因子: --
作者: [Abdullahi, U.]
通讯作者: Abdullahi, U.
Using Machine Learning and UN data to Predict Local Violence in the Central African Republic
使用机器学习和联合国数据预测中非共和国的当地暴力事件
DOI: --
发表时间:
期刊:
影响因子: --
作者: [Abbs L;]
通讯作者: Abbs L;
"Guns, Placards and Olive Branches? Nonviolent Activism and Civil War Termination"
“枪支、标语牌和橄榄枝?非暴力行动和终止内战”
DOI: --
发表时间:
期刊:
影响因子: --
作者: [Abbs L;]
通讯作者: Abbs L;
"Where Do UN Peacekeeping Patrols Go?"
《联合国维和巡逻队去哪里?》
DOI: --
发表时间:
期刊:
影响因子: --
作者: [Abbs L;]
通讯作者: Abbs L;
共 6 条
    Business and Local Government Data Research Centre Legacy Status Proposal
    • 批准号:
      ES/Y003411/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $13.65万
    • 财政年份:
      2024
    • 负责人:
      Maria Fasli
    • 依托单位:
    Business and Local Government Data Research Centre
    • 批准号:
      ES/S007156/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $155.52万
    • 财政年份:
      2019
    • 负责人:
      Maria Fasli
    • 依托单位:
    Utilising Big Data in the Practice of Torture Survivors' Rehabilitation
    • 批准号:
      ES/M010422/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $26.91万
    • 财政年份:
      2015
    • 负责人:
      Maria Fasli
    • 依托单位:
    DADO - Data Analytics Driven by Ontologies
    • 批准号:
      EP/M507702/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $11.07万
    • 财政年份:
      2014
    • 负责人:
      Maria Fasli
    • 依托单位:
    国内基金
    海外基金
    Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
    Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
    Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
    • 批准号:
      --
    • 项目类别:
      --
    • 资助金额:
      40万元
    • 批准年份:
      2020
    • 负责人:
      Vikrant Gupta
    • 依托单位:
    基于Linked Open Data的Web服务语义互操作关键技术
    • 批准号:
      61373035
    • 项目类别:
      面上项目
    • 资助金额:
      77.0万元
    • 批准年份:
      2013
    • 负责人:
      冯志勇
    • 依托单位: