Newton STFC-NARIT: Using astronomy surveys to train Thai researchers in Big Data analysis

Newton STFC-NARIT：利用天文学调查来培训泰国研究人员进行大数据分析

• 批准号: ST/P005594/1
• 负责人: James Mullaney
• 金额: $ 4.58万
• 依托单位: University of Sheffield
• 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%2FP005594%2F1
• 关键词: Newton; STFC; NARIT; Using; astronomy

The most effective way of reducing levels of poverty in developing countries is through their continued economic growth, which leads to increased levels of income per person. To remain competitive, however, a developing economy needs access to a workforce with increasingly sophisticated skills. For Thailand today, this means skills that enable innovation, allowing it to compete against other developing and developed economies. With more and more sectors collecting data on their customers, production lines, distribution networks, stock prices, etc., one of the most crucially needed of these "high-level" skills is the ability to handle large amounts of digital data. However, as present, Thai students lack ready access to very large datasets, which prevents their training in this area. Our project addresses this problem by combining the resources and experience of UK astronomers of very large datasets, with the skills of Thai Data Scientists in digital data analysis. Through this collaboration, the Thai students will gain access to a vast amounts of digital data in the form of astronomical surveys. Working under the supervision of the Thai and UK partners, the students will develop software that will automatically analyse this data and, in doing so, gain important experience in handling vast quantities of digital data. Furthermore, the software resulting from the students' research will form an important component of the pipeline used to process data from a new telescope being developed by UK astronomers, and will thus directly benefit UK science. On completion of the project, the skills acquired by the Thai students will be readily transferrable to a diverse range of economic sectors such as information technology, medicine, finance, security, etc., thereby helping the further economic development of Thailand.

减少发展中国家贫穷程度的最有效办法是通过持续的经济增长，从而提高人均收入水平。然而，为了保持竞争力，发展中经济体需要获得技能日益复杂的劳动力。对今天的泰国来说，这意味着能够促进创新的技能，使其能够与其他发展中国家和发达经济体竞争。随着越来越多的行业收集客户、生产线、分销网络、股票价格等数据，在这些“高级”技能中，最迫切需要的技能之一是处理大量数字数据的能力。然而，目前，泰国学生缺乏现成的访问非常大的数据集，这阻碍了他们在这方面的培训。我们的项目通过将英国天文学家在超大型数据集方面的资源和经验与泰国数据科学家在数字数据分析方面的技能相结合来解决这个问题。通过这种合作，泰国学生将以天文调查的形式获得大量的数字数据。在泰国和英国合作伙伴的监督下，学生们将开发自动分析这些数据的软件，并在此过程中获得处理大量数字数据的重要经验。此外，学生们的研究成果将成为处理英国天文学家正在开发的新望远镜数据的管道的重要组成部分，从而直接使英国科学受益。在项目完成后，泰国学生获得的技能将很容易转移到各种经济部门，如信息技术，医药，金融，安全等，从而促进泰国经济的进一步发展。

项目成果

Transient Detection Modelling for Gravitational-wave Optical Transient Observer (GOTO) Sky Survey

• DOI: 10.1145/3195106.3195153
• 发表时间: 2018-02
• 期刊: Proceedings of the 2018 10th International Conference on Machine Learning and Computing
• 作者: Aireen B. Tabacolde;Tossapon Boongoen;Natthakan Iam-on;J. Mullaney;U. Sawangwit;K. Ulaczyk