Business and Local Government Data Research Centre
Business and Local Government Data Research Centre
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 --
中文摘要
英国政府的产业战略中提出了成为世界上最具创新能力的经济体的雄心。地方当局和企业拥有大量数据,涵盖其日常活动的方方面面。虽然这种资源很有价值,但公共和私营部门商业模式的变革性变化的机会来自于采用数据科学和人工智能技术,并将它们作为分析层嵌入决策的每个阶段。在高级分析的帮助下,将数据转化为知识可以为地方当局和企业提供更多信息,帮助他们制定更好的政策,改善业务运营。商业和地方政府数据研究中心(BLG DRC)旨在通过高级分析,逐步改变公共部门组织和企业使用和驾驭数据的方式。因此,BLG DRC将在埃塞克斯大学内整合社会科学、数据科学和人工智能的多个研究分支,并将提供在社会科学和方法论研究方面取得重大新突破所需的协同范围。BLG DRC的主要利益相关者仍将是地方当局和企业,但我们将把我们的工作和合作范围扩大到更广泛的公共部门以及国际。BLG DRC的使命是将利益相关者和用户放在核心位置,研究工作计划将以用户为导向,并涉及与外部合作伙伴和利益相关者共同创建的氛围。由培训和知识交流活动组成的全面综合外联方案将确保与包括决策者在内的研究和项目伙伴的用户和利益攸关方进行持续对话,并确保项目产出将在中心成立后产生持久影响。特别是,BLG DRC将专注于公共部门,并与我们的地区合作伙伴埃塞克斯县议会(ECC)、埃塞克斯警察局(EP)、埃塞克斯伙伴大学NHS基金会信托基金(EPUT)和其他机构合作,作为一个联合的、全系统的公共部门人工智能和数据科学中心,工作重点将是通过嵌入新的数据科学技术和人工智能来改善公共服务的生活和提高效率。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。我们的目标是探索这些企业面临的障碍,以及数据科学和人工智能如何帮助我们了解克服这些障碍的最佳手段。整个工作方案分为两个相互关联的方面:(1)发展新的研究和跨学科能力;(2)实施和进一步扩大我们的综合外联方案。该方案旨在最大限度地发挥现有活动的影响,并开展将在区域和国家一级产生直接和重大影响的新研究。我们的用户和利益攸关方将继续在制定工作方案方面发挥关键作用,一方面受益于研究和综合外联方案,另一方面直接提出社会经济研究方面的挑战和问题,并开发解决这些问题所需的新方法,以便能够最大限度地承担我们的工作。在我们成功的实质性社会经济研究方案和方法研究流的基础上,我们的目标是在三个核心领域进一步开发和开展新的研究:(I)支持弱势群体;(Ii)支持经济增长;(Iii)数据科学和人工智能的方法和技术。BLG DRC的新阶段将是一项令人兴奋的发展,不仅将促进知识的发展,还将造福于我们的社区。
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.
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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
DOI:
--
发表时间:
2024
期刊:
影响因子:
--
作者:
[Back]
通讯作者:
Back
共 7 条
Business and Local Government Data Research Centre Legacy Status Proposal
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批准号:ES/Y003411/1
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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
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批准号:ES/M010422/1
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项目类别:Research Grant
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资助金额:$26.91万
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财政年份:2015
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负责人:Maria Fasli
-
依托单位:
DADO - Data Analytics Driven by Ontologies
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批准号:EP/M507702/1
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项目类别:Research Grant
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资助金额:$11.07万
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财政年份:2014
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负责人:Maria Fasli
-
依托单位:
Innovative tools to enable exploration of complex and specialised data sets
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批准号:EP/M507106/1
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项目类别:Research Grant
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资助金额:$13.62万
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财政年份:2014
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负责人:Maria Fasli
-
依托单位:
Smart Data Analytics for Business and Local Government
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批准号:ES/L011859/1
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项目类别:Research Grant
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资助金额:$662.36万
-
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
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批准号:11872210
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项目类别:面上项目
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资助金额:63.0万元
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批准年份:2018
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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
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批准号:81601936
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项目类别:青年科学基金项目
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资助金额:17.0万元
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批准年份:2016
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负责人:曾羿
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依托单位: