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

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.

The immediate impact of this research will be on the Thai scientists and students who will receive training in high-level data handling skills either via their research projects or by attending one of the 5-day workshops. Following this training, the scientists and students will be able to apply these skills within a diverse range of growth sectors, such as finance, medicine, logistics, information technology etc. In doing so, they will benefit the wider Thai economy by helping it grow and compete internationally through innovation.

Further impact will be felt by the scientists and astronomers who are involved in GOTO - of which NARIT is a major contributing member. By establishing a data centre to host and automatically analyse large amounts of digital data, the outcome of the students' research will play an important role in extracting information from the vast amounts of data that GOTO will provide. This information can then be fed through to other NARIT facilities for follow-up observations, including by their network of Robotic Telescopes within outreach centres across Thailand. This latter point opens the prospect of the project raisng awareness amongst students, schoolchildren and the general public of the impact that Big Data can have on scientific research.