Newton STFC-Narit: Using astronomy surveys to train Thai researchers in handling Big Data

降低发展中国家贫困程度的最有效方式是通过持续的经济发展，从而提高人均收入水平。然而，为了保持竞争力，一个发展中经济体需要拥有一支技能越来越精湛的劳动力队伍。对于今天的泰国来说，这意味着能够实现创新的技能，使其能够成功地与其他发展中和发达经济体竞争。随着越来越多的行业收集关于其客户、生产线、分销网络、股票价格等的数据，最迫切需要的“高级”技能之一是处理大量数字数据的能力。然而，泰国数据科学家和学生通常缺乏对非常大的数据集的现成访问，这给他们在这一领域的培训带来了障碍。同样，其他科学家--包括天文学家--通常缺乏必要的数据处理技能，无法有效地存储和分析他们收集的大量数据。我们的项目通过将英国和泰国天文学家对超大型数据集的访问和理解与泰国数据科学家在数据库处理和机器学习方面的技能相结合来解决这两个问题，以培训泰国学生先进的数据处理技术。在泰国和英国合作伙伴的监督下，参与该项目的研究生将在Narit建立一个数据中心，存储和自动分析引力波光学瞬变天文台(GOTO)每晚产生的数百GB数据。GOTO是一台主要的新观测望远镜，Narit是该望远镜的成员之一。在这个过程中，学生将获得数据库管理和基于机器学习的自动化数据分析的重要经验。由此产生的数据中心将是Narit天文学家的重要研究资产，也是更广泛的泰国科学界的关键培训资源。事实上，我们将利用数据中心作为培训辅助工具，在两个为期五天的实践讲习班(每年一个补助金，每个名额最多可容纳30名受训人员)中向其他60名研究人员和学生传授数据处理技能。通过三个研究生研究项目，我们的团队将把数据中心开发成一个自动化存储和分析系统，最终目标是与Narit的其他观测设施一起输出后续观测的优先目标列表。这样，泰国数据中心将成为基于机器学习的分析的试验台，在数据处理研究方面保持在所有GOTO数据中心的前列。项目完成后，泰国学生获得的技能将很容易转移到不同的经济部门，如信息技术、医药、金融、安全等，从而帮助泰国进一步发展经济。

The most effective way of reducing levels of poverty in developing countries is through their continued economic development, 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 successfully 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 "high-level" skills is the ability to handle large amounts of digital data. However, Thai data scientists and students typically lack ready access to very large datasets, which presents a barrier to their training in this area. Similarly, other scientists - including astronomers - typically lack the necessary data handling skills to efficiently store and analyse the large amounts of data they collect. Our project addresses both these problems by combining UK and Thai astronomers' access to and understanding of very large datasets with Thai data scientists' skills in databasing and machine learning to train Thai students in advanced data handling techniques.Working under the supervision of the Thai and UK partners, the graduate students involved in the project will establish a data centre at NARIT to store and automatically analyse the hundreds of gigabytes of data generated each night by the Gravitational-wave Optical Transient Observatory (GOTO) - a major new survey telescope of which NARIT is a contributing member. In the process, the students will gain vital experience of database management and automated, machine learning-based data analyses. The resulting data centre will be an important research asset for NARIT astronomers and a key training resource for the broader Thai scientific community. Indeed, we will ourselves use the data centre as a training aid in teaching data handling skills to up to 60 other researchers and students during two 5-day practical workshops (one held each year of the grant with space for up to 30 trainees each). Through three graduate research projects, our team will develop the data centre into an automated storage and analysis system with the ultimate goal of outputting a prioritised list of targets for follow-up observations with NARIT's other observing facilities. In doing so, the Thai data centre will be a testbed for machine learning-based analyses, remaining at the forefront of all GOTO data centres in terms of data handling research. 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.