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Details of Grant 

EPSRC Reference: EP/T003707/1
Title: Statistics and Data Science training to build research capacity to address societal problems in Mongolia
Principal Investigator: Faraway, Professor JJ
Other Investigators:
Smith, Dr T Uuye, Dr O Kyprianou, Professor A
Researcher Co-Investigators:
Project Partners:
Mongolia National Development Agency National Statistics Office of Mongolia UNICEF (Global)
Department: Mathematical Sciences
Organisation: University of Bath
Scheme: GCRF (EPSRC)
Starts: 01 April 2020 Ends: 31 March 2022 Value (£): 130,558
EPSRC Research Topic Classifications:
Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Technical Consultancy Education
Related Grants:
Panel History:
Panel DatePanel NameOutcome
12 Jun 2019 SI GCRF 4 - Maths Research and GCRF 5 - Maths Capability Announced
Summary on Grant Application Form
Mongolia is a developing country that is large in area but small in population. Since the fall of communism, Mongolia has experienced difficulty in developing both an effective civil service and a university system that generates the expertise to solve the problems of a modern society. Much information is gathered but institutions and stakeholders lack the experience to extract knowledge from this data and use it effectively in the public interest. We propose a programme of workshops that will train Mongolian academics, civil servants and other stakeholders in the use of statistics, machine learning and data science. The programme will be customised to work on some of the current most pressing Mongolian social challenges, using real data accumulated by Mongolian public institutions. This will ensure that the technical knowledge shared is not abstract but applied with the potential for immediate impact on Mongolian society.

The programme will have 4 stages.

In the first stage we will scope out the problems and assemble the data. We have the advantage of our prior collaborations with Mongolia which will already offers a head start.

We follow this in the second stage with a two week session of instruction in the capital of Mongolia, Ulaanbaatar. This will be given by expert academics with the support of well-trained doctoral students. The instruction will be highly interactive using modern teaching techniques to accommodate for the diversity in previous experience of participants as well as diversity in English language ability. Graduate students from the University of Bath will play a significant role in teaching and interacting with the Mongolians as they learn. The team has previous experience in delivering similar activities to civil service data scientists at the Paraguayan Ministry of Development. Best practice from this context will be integrated into the delivery in Mongolia.

In the third stage, four leading Mongolian stakeholders will visit Bath for a week to attend one of Bath's innovative Integrative Think Tanks (ITT). The latter is a unique interactive research training workshop that has been developed and already used multiple times for Bath's EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa). Such workshops are based around the principle of taking real world challenges in industry, or in this case, the public sector, and, through a tried and tested process of facilitation, distilling out well-formulated mathematical research questions that can move forward into an active and collaborative research projects.

The ITT in Bath will use as its starting challenges the specific Mongolian data and societal problems described earlier. This will also involve a larger number of Bath academics and (SAMBa) graduate students who will contribute to and learn from the aforementioned process of distilling out tangible mathematical questions. Having run nine ITTs, and with the accolade of generating manifold new research projects with accompanying funding support, the Department of Mathematical Science at Bath has a strong track record in the delivery of ITTs.

The final stage will be a week long visit back to Ulaanbaatar to further advance the research agenda on the Mongolian problems by feeding them back into an ITT attended by a wide spread of Mongolian stake-holders together with Bath academics and doctoral student.

Throughout, we will be in electronic communication with our Mongolian partners to advance the instruction and progress on research.

At the end of the programme, we will have trained a group of Mongolian academics and civil servants in statistics and data science. We will have advanced understanding on a range of Mongolian problems using their data. Knowledge will be transferred in that the academics will be able to pass it on to their students and the civil servants will have developed data-driven policy making skills.

Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Organisation Website: http://www.bath.ac.uk