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Business and Local Government Data Research Centre

Business and Local Government Data Research Centre
商业和地方政府数据研究中心
批准号:
ES/S007156/1
负责人:
Maria Fasli
金额:
$155.52万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2019
资助国家:
英国
项目状态:
未结题
起止时间:
2019 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
An ambition to be the world's most innovative economy is set out in the UK Government Industrial Strategy. Local authorities and businesses possess large amounts of data covering every aspect of their daily activities. While this resource is valuable, the opportunity for transformative change in business models in public and private sectors comes from adopting data science and artificial intelligence techniques and embedding them as an analytical layer in every stage of decision making. Transforming data to knowledge with the help of advanced analytics can provide local authorities and businesses additional information which can help them to design better policies and improve their business operations.The Business and Local Government Data Research Centre (BLG DRC) aims to enable a step change in the way public sector organisations and businesses make use of and harness the power of their data through advanced analytics. As such, BLG DRC will coalesce a number of research strands in social sciences, data science and AI within University of Essex and will provide the synergetic scope required to make significant new breakthroughs in social sciences and methodological research. The primary stakeholders of BLG DRC will continue to be local authorities and businesses, but we will expand our remit of work and collaborations to the wider public sector as well as internationally.BLG DRC's mission places stakeholders and users at its heart, and the research programme of work will be user-driven and involve an ethos of co-creation with external partners and stakeholders. The comprehensive integrated outreach programme which consists of training and knowledge exchange activities will ensure an ongoing dialogue with the users and stakeholders of the research and project partners including policy makers and that the project outputs will have lasting impact beyond the life of the Centre. In particular, focusing on the public sector and working with our regional partners, Essex County Council (ECC), Essex Police (EP), Essex Partnership University NHS Foundation Trust (EPUT) and others, BLG DRC will serve as a joined up, system-wide public sector AI and data science hub where the focus of the work will be on improving lives and generating efficiency in public services through embedding of novel data science techniques and AI. 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. We aim to explore the barriers these businesses face and how data science and AI can help us understand the best means of overcoming these. The overall programme of work is divided into two strands which are strongly interlinked: (i) developing new research and interdisciplinary capacity, and (ii) delivering and further expanding our integrated outreach programme. The programme has been designed to maximise the impact of both existing activity and also engage in new research that will have direct and significant impact at the regional and national level. Our users and stakeholders will continue to play a key role in shaping up the programme of work on the one hand benefitting from the research and integrated outreach programme while on the other directly feeding in challenges and problems with respect to socio-economic research and the development of new methods needed to address these problems so that the take-up of our work can be maximised. Building on our successful substantive socio-economic programme of research and methodological research stream, we aim to further develop and undertake new research in three core areas: (i) Support for Vulnerable People; (ii) Supporting Economic Growth; (iii) Methodologies and Techniques for Data Science and AI. The new phase of BLG DRC promises to be an exciting development that will not only advance knowledge but also benefit our community.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
Probabilistic Named Entity Recognition for nonstandard format entities using cooccurrence word embeddings
使用共现词嵌入对非标准格式实体进行概率命名实体识别
DOI: 10.1109/bigdata47090.2019.9005587
发表时间: 2019
期刊:
影响因子: --
作者: [AlAni J]
通讯作者: AlAni J
Special issue on "Learning in data science: theory, methods and applications"-preface by the guest editors
《数据科学学习:理论、方法与应用》特刊——客座编辑序言
DOI: 10.1007/s11634-020-00431-6
发表时间: 2020
期刊: Advances in Data Analysis and Classification
影响因子: 1.6
作者: [Baier D]
通讯作者: Baier D
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.
Foreign Direct Investment and Knowledge Diffusion in Poor Locations
贫困地区的外国直接投资和知识传播
DOI: 10.3386/w24461
发表时间:
期刊:
影响因子: --
作者: [Abebe G]
通讯作者: Abebe G
7
    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:
    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:
    Innovative tools to enable exploration of complex and specialised data sets
    • 批准号:
      EP/M507106/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $13.62万
    • 财政年份:
      2014
    • 负责人:
      Maria Fasli
    • 依托单位:
    国内基金
    海外基金
    具有粘性逆Lax-Wendroff边界处理和紧凑WENO限制器的自适应网格local discontinuous Galerkin方法
    • 批准号:
      11872210
    • 项目类别:
      面上项目
    • 资助金额:
      63.0万元
    • 批准年份:
      2018
    • 负责人:
      朱君
    • 依托单位:
    miRNA-140调控软骨Local RAS对骨关节炎中骨-软骨复合单元血管增生和交互作用影响的研究
    • 批准号:
      81601936
    • 项目类别:
      青年科学基金项目
    • 资助金额:
      17.0万元
    • 批准年份:
      2016
    • 负责人:
      曾羿
    • 依托单位: