From Stars to Baht: Broadening the economic impact of astronomical data handling techniques in Thailand

Lead Research Organisation: University of Sheffield
Department Name: Physics and Astronomy

Abstract

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. Research has shown that one of the main ways of achieving this is through maintained increases in levels of productivity (defined as output per hour worked) within businesses and organisations. For an upper-middle income economy such as Thailand's, productivity growth will increasingly rely on innovation, which today requires access to high-tech skills. With more and more Thai industries collecting data on their customers, production lines, distribution networks, stock prices, etc., one of the most crucially needed high-tech skills is the ability to handle large amounts of digital data. Our ongoing project aims to provide such skills for businesses and organisations in the Northern region of Thailand which has traditionally suffered from weaker economical growth compared to other regions such as Bangkok. The first step in this project -- for which we received Newton funding -- was to use large astronomical datasets to expose Thai data scientists and their postgraduate students to "Big Data". Following the success of that first stage, we now request GCRF funding to facilitate working with five pre-selected businesses and organisations to research how we can adapt the technologies and skills we have developed to meet their data handling and analysis needs. In doing so, we will be using our team's skills and technologies to have a real economic impact on these external partners, while we build our capacity for working with businesses and organisations. This experience will be excellent preparation for our ultimate goal of establishing a fully self-sustaining "Centre of Excellence" for researching technologies to meet the data handling and analysis needs of businesses and organisations in Northern Thailand.

Planned Impact

Please see our Pathways to Impact statement.

Publications

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Description Actually there are no new Key Findings, but the system won't let me select "No" to the first question.
Exploitation Route N/A
Sectors Other

 
Description Actually, there are no new impacts, but the system won't save my changes if I select "No" to the first question.
Sector Other
Impact Types Economic

 
Description Newton STFC-Narit: Using astronomy surveys to train Thai researchers in handling Big Data
Amount £89,342 (GBP)
Funding ID ST/R006539/1 
Organisation Science and Technologies Facilities Council (STFC) 
Sector Public
Country United Kingdom
Start 01/2018 
End 12/2020
 
Title TAPP Auto database 
Description Database containing price information for a wide range of car makes and models. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
Impact TAPP auto will use the database to help them to price their cars for purchase/sale. 
 
Title Thanapirya Data Model 
Description Developed a machine-learning-based model trained on purchase and store location records. The train model can now be used by Thanapirya to predict how a new store should be stocked given the local demographics. 
Type Of Material Computer model/algorithm 
Year Produced 2019 
Provided To Others? Yes  
Impact The model has been made available to Thanapirya. They have yet to utilise the model for financial gain, since it has only been made available to them within the past week. 
 
Description GCRF Phase 1 
Organisation Mae Fah Luang University
Department M Store, Mae Fah Luang University
Country Thailand 
Sector Academic/University 
PI Contribution Our research team, which consisted of staff members and thirteen undergraduate students, worked with the five external partners to help address
Collaborator Contribution x
Impact x
Start Year 2018
 
Description GCRF Phase 1 
Organisation Mae Fah Luang University
Country Thailand 
Sector Academic/University 
PI Contribution Our research team, which consisted of staff members and thirteen undergraduate students, worked with the five external partners to help address
Collaborator Contribution x
Impact x
Start Year 2018
 
Description GCRF Phase 1 
Organisation Pibulsongkram Rajabhat University
Country Thailand 
Sector Academic/University 
PI Contribution Our research team, which consisted of staff members and thirteen undergraduate students, worked with the five external partners to help address
Collaborator Contribution x
Impact x
Start Year 2018
 
Description GCRF Phase 1 
Organisation Thanapirya Public Company Limited
Country Thailand 
Sector Private 
PI Contribution Our research team, which consisted of staff members and thirteen undergraduate students, worked with the five external partners to help address
Collaborator Contribution x
Impact x
Start Year 2018
 
Description GCRF Phase 1 Kick-off meetings between students and external partners 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Undergraduate students
Results and Impact The thirteen undergraduate students involved in the project met with their respective external partners to question them about their data analysis needs and available data.
Year(s) Of Engagement Activity 2018