DARA Big Data: Colombia

DARA 大数据：哥伦比亚

• 批准号: ST/R001944/1
• 负责人: Anna Scaife
• 金额: $ 47.15万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FR001944%2F1
• 关键词: DARA; Big; Data; Colombia

The programme will build a multi-institute big data research and training network between Colombian and UK partners that will establish sustainable links via a Data Science Network, led by academics and developed and refined in consultation with industry. eResearch capacity is an absolute necessity in a world where the appropriate handling of big data - in the natural sciences, medicine, the humanities and the social sciences - is of paramount importance. This program will support the development of research capacity in Big Data and Data Science in Colombia through the creation of a joint UK-Columbia training network which will form the basis of a long term sustainable research collaboration. The program is designed to create a UK-Colombia Data Science Network to advance research and training in big data science. The program does not intend to build physical infrastructure, but will utilise capacity at existing facilities developed for data intensive research in conjunction with Colombian partners.

该计划将在哥伦比亚和英国合作伙伴之间建立一个多机构大数据研究和培训网络，该网络将通过数据科学网络建立可持续的联系，该网络由学者领导，并与行业协商开发和完善。在自然科学、医学、人文和社会科学中适当处理大数据至关重要的世界中，电子研究能力是绝对必要的。该计划将通过创建英国-哥伦比亚联合培训网络来支持哥伦比亚大数据和数据科学研究能力的发展，该网络将构成长期可持续研究合作的基础。该计划旨在创建一个英国-哥伦比亚数据科学网络，以推进大数据科学的研究和培训。该计划并不打算建设实体基础设施，而是将利用与哥伦比亚合作伙伴共同开发的数据密集型研究现有设施的能力。

项目成果

The Cloud Factory I: Generating resolved filamentary molecular clouds from galactic-scale forces

云工厂 I：利用银河尺度的力生成解析的丝状分子云

• DOI: 10.1093/mnras/stz3328
• 发表时间: 2020
• 期刊: Monthly Notices of the Royal Astronomical Society
• 影响因子: 4.8
• 作者: Smith R

FILAMENTARY STAR-FORMING GAS CLOUDS: TURBULENCE AND MAGNETIC FIELDS

丝状恒星形成气云：湍流和磁场

• 发表时间: 2019
• 作者: Andrés F. Izquierdo Cartagena

MACHINE LEARNING AND BIG DATA TECHNIQUES FOR SATELLITE-BASED RICE PHENOLOGY MONITORING

用于卫星水稻物候监测的机器学习和大数据技术

• 发表时间: 2019
• 作者: Andrés Aguilar Ariza

Development of a Powerwall-based solution for the manual flagging of radio astronomy data from eMerlin

开发基于 Powerwall 的解决方案，用于手动标记来自 eMerlin 的射电天文学数据

• 发表时间: 2019
• 作者: Mosquera, F

The Cloud Factory II: gravoturbulent kinematics of resolved molecular clouds in a galactic potential

云工厂 II：银河势中解析分子云的重力湍流运动学

• DOI: 10.1093/mnras/staa3470
• 发表时间: 2021
• 期刊: Monthly Notices of the Royal Astronomical Society
• 影响因子: 4.8
• 作者: Izquierdo A