Authors: Sujung An, Ahjung Lee
Photo: UN Women/Sujung An
English | 한국어
The UN Women Knowledge and Partnerships Centre (the Centre) in the Republic of Korea, in collaboration with UN Women’s Women Count Programme, Statistics Korea (KOSTAT) and the United Nations Statistical Institute for Asia and the Pacific (UNSIAP), successfully hosted the “Regional Training on Big Data and Data Science for Gender Statistics in Asia and the Pacific”.
Held from 21 to 25 April in Daejeon, a central city 137 kilometers south of Seoul, the training brought together 22 officials from National Statistics Offices (NSOs) representing 13 countries across the region, including: Bangladesh, Fiji, India, Indonesia, Kyrgyzstan, Maldives, Nepal, Philippines, Sri Lanka, Thailand, Timor-Leste, Uzbekistan and Viet Nam.
Sujung An, a Programme Officer at the Knowledge and Partnerships Centre, welcomed participants on behalf of Vu Phuong Ly, Office in Charge of the Centre. “This training provides a unique opportunity to collectively build capacities in using digital technology to strengthen gender statistics for better, evidence-based policymaking.”
Participants are learning key concepts related to gender equality and gender statistics. Photo: UN Women/Sujung An
What do big data, data science and gender equality have in common?
Gender data are crucial for understanding societal dynamics and informing inclusive policymaking. According to Sneha Kaul, Statistics Analyst at UN Women Regional Office for Asia and the Pacific, high-quality and comparable statistics enable policymakers to address disparities faced by women, men and gender-diverse groups effectively. However, many countries continue to face significant barriers in collecting sufficient and reliable gender data.
Traditional statistical methods often fall short in capturing the nuances and realities of today’s fast-evolving societies. As highlighted during the training, big data and data science can offer innovative solutions to fill these gaps. Non-traditional data sources — such as social media activity, mobile data and satellite imagery — provide new avenues for collecting timely, detailed insights. These sources, enabled by digital technologies, are increasingly being used to enhance the production, analysis and dissemination of gender data while addressing data gaps that have long persisted.
This training, therefore, was designed to explore how these new technologies can be practically applied to gender data production and analysis, offering both conceptual frameworks and hands-on experience.
Participants are introduced to the fundamental elements of big data and its application in gender statistics. Photo: UN Women/Sujung An
The week-long training, consisting of 23 sessions, combined theoretical lectures with interactive, practical exercises. Key sessions covered topics such as: the fundamentals of big data, machine learning and geospatial data applications for gender-focused insights, and practical uses of web scraping and AI-driven tools to extract gender indicators from online platforms.
Statistics Korea presented a case study detailing collaborations with private sector organizations to utilize credit card transactions, GPS logs and telecom data. These non-traditional data sources have been instrumental in generating disaggregated gender data for studies on commuting patterns and daily mobility, a topic that attracted considerable attention from attendees.
Christophe Bontemps, a statistical lecturer at UNSIAP, is delivering a session on the principles of machine learning. Photo: UN Women/Sujung An
Participants’ perspectives
On the final day, participants shared their reflections on the tools and techniques they acquired during the training. Several participants expressed plans to implement these methods in their respective countries.
A participant from India noted: “Using what I learned about web scraping and mobile payment data, I plan to analyse gaps in rural women’s economic activity and financial inclusion. I’m also interested in using health app data to improve maternal health statistics.”
Similarly, an attendee from Indonesia emphasized the importance of institutional frameworks, saying: “I’ll apply the methods for collecting mobile and financial transaction data to analyse gendered patterns of mobility and economic activity. Strengthening the legal and institutional frameworks for big data use in official statistics is also a priority.”
A participant from Fiji highlighted the potential for using these tools in disaster responses: “With satellite imagery, social media data and machine learning, we can monitor women’s mobility and digital access in disaster situations and better respond to gender-based violence and climate emergencies.”
Statistics Korea (KOSTAT) is sharing its practices in producing big data-enabled statistics. Photo: UN Women/Sujung An
Data: A tool for reflection and action
While the training provided participants with valuable technical knowledge, the discussions also underlined the broader challenges of integrating big data into gender statistics systems. Topics such as data privacy, ethical considerations and governance frameworks emerged as central to advancing digital solutions.
According to both participants and trainers, building systems capable of leveraging big data requires not only technological upgrades but also institutional readiness and capacity-building. Many countries agreed that sustained collaboration and knowledge-sharing across the region are essential to establishing robust frameworks for gender statistics.
This regional training demonstrated the transformative potential of big data and data science in addressing gender disparities and improving policy outcomes. By equipping national statistics officials with practical skills and fostering a deeper understanding of digital tools, the programme laid the foundation for sustainable improvements in gender data systems.
Accurate gender data are not just a mirror of societal realities but also an engine for change, empowering governments to create inclusive and evidence-based policies that leave no one behind.