15–27 September 2025 | Holiday Inn Resort Baruna Bali, Indonesia

As the world steps deeper into the era of Big Data, the demand for more timely, accurate, and relevant statistics has become increasingly essential for evidence-based decision-making. Recognizing this transformation, the Regional Hub on Big Data and Data Science for Asia and the Pacific—hosted by Statistics Indonesia (BPS) and Politeknik Statistika STIS—organized a two-week Short Course on Mobile Positioning Data (MPD) for Official Statistics in Bali from September 15–27, 2025.

This program represents the technical continuation of the Regional Hub’s broader initiative to strengthen both policy and technical capacities in the region. Following the Executive Training for Policy Makers held in Jakarta in July 2025, which discussed strategic directions and governance frameworks, the Bali course focused on building practical competencies for technical staff to transform raw mobile positioning data into actionable insights.

Harnessing the Power of Mobile Positioning Data

Mobile Positioning Data (MPD) is generated whenever mobile network subscribers interact with cellular networks, through calls, messages, or internet usage. This massive, high-frequency, and spatially detailed data offers immense potential for official statistics, particularly in analyzing population mobility, tourism flows, commuting behavior, and urban dynamics.

In Indonesia, the use of MPD has already proven successful in enriching tourism statistics, helping policymakers monitor tourist movements more accurately and develop evidence-based strategies for sustainable economic growth. Building upon this experience, the Regional Hub aims to extend similar capacities across neighboring countries through structured training and knowledge-sharing.

Building Skills and Collaboration Across Borders

The two-week course brought together 14 technical professionals from National Statistical Offices (NSOs), tourism authorities, and Mobile Network Operators (MNOs) in the Philippines, Cambodia, and Timor-Leste. Their diverse background: spanning ICT, statistics, and data processing, ensured that the learning outcomes could be directly applied to each institution’s work.

Participants received intensive, hands-on training in data science tools such as SQL, Python, and PySpark, focusing on how to manage large datasets and conduct analyses including clustering, stop-spot detection, and event identification. The sessions were designed not only to enhance technical skills but also to deepen participants’ understanding of how MPD can be integrated into official statistics—particularly in tourism, a key economic sector across the region.

Beyond the technical modules, the program fostered regional cooperation and dialogue. By working together on country-specific feasibility studies, participants explored how MPD-based indicators could be introduced into their national statistical systems, identifying challenges such as data access, privacy frameworks, and the need for cross-sector collaboration. These discussions highlighted the importance of sustained partnerships between governments, statistical agencies, and private sector data providers.

From Theory to Practice

Throughout the 13 effective training days, participants progressed through a structured curriculum that began with data science foundations and culminated in advanced MPD applications. The first week introduced concepts in database systems, Python-based data analysis, and distributed computing with PySpark. In the second week, the focus shifted to MPD-specific applications, linking big data analytics to real-world policy needs such as tourism monitoring and mobility studies.

Each country team produced a feasibility assessment outlining potential pathways for integrating MPD into official statistics, mapping opportunities for collaboration with mobile network operators, and identifying technical and institutional readiness. These concrete outputs provided valuable starting points for future national initiatives and pilot projects.

Strengthening Regional Readiness for Big Data

The outcomes of the course extend well beyond the classroom. Participants returned home equipped not only with new analytical skills but also with a shared vision for how MPD can transform official statistics. The program laid the groundwork for future cooperation, fostering a growing community of practice committed to advancing data innovation in the Asia-Pacific region.

Through this experience, the Regional Hub continues to build momentum toward a more data-driven ecosystem—one where policy and technology go hand in hand to support inclusive and sustainable development.

Appreciation and Collaboration

The success of the Short Course on MPD was made possible through the support of Indonesia AID as the funding partner, the commitment of BPS–Statistics Indonesia, and the dedication of the Regional Hub Secretariat at Politeknik Statistika STIS.

Special appreciation goes to the trainers and facilitators from BPS and STIS, whose guidance extended beyond technical instruction to mentorship throughout the exercises. Above all, the organizers express deep gratitude to all participants for their active engagement, collaboration, and enthusiasm, reflecting the shared spirit of advancing official statistics in the digital era.

Jakarta, July 9, 2025 – In the era of rapid digital transformation, the need for new, faster, more accurate, and relevant data sources has become increasingly vital for evidence-based decision-making. Recognizing this urgency, the Regional Hub on Big Data and Data Science for Asia and the Pacific held an Executive Training on Mobile Positioning Data (MPD) for Official Statistics from July 8-10, 2025, at the Gran Melia Hotel Jakarta.

The event was opened by Acting Chief Secretary Edy Mahmud and UN Resident Coordinator in Indonesia Gita Sabharwal, followed by a keynote speech delivered by Acting Deputy for Statistical Methodology and Information Pudji Ismartini. This activity is part of an initiative to strengthen the capacity of countries in the Asia and Pacific region to adopt new approaches in official statistics through the utilization of big data. The training was attended by stakeholders from diverse backgrounds, including representatives from National Statistical Offices (NSOs), ministries of tourism, and Mobile Network Operators (MNOs) from the Philippines, Cambodia, and Timor-Leste.

Understanding Mobile Positioning Data (MPD)

During the first two days, panel sessions featured speakers from Indonesian mobile operators, government agencies, and data governance experts. The main focus of the training was Mobile Positioning Data (MPD)—a form of big data generated from interactions between mobile devices and cellular network infrastructure, such as signals during calls, message sending, or internet usage. MPD has a unique advantage as it can capture human mobility in space and time with high precision, making it a potential data source for various statistical indicators, especially in the tourism, transportation, and population mobility sectors.

In Indonesia, the utilization of MPD has shown tangible results. Through collaboration between BPS-Statistics Indonesia and cellular network providers, Indonesia has successfully leveraged MPD to enrich tourism statistics, such as calculating foreign and domestic tourist visits in a more real-time manner. This best practice was shared with participating countries to encourage replication and adaptation in their respective nations.

The discussions explored various important dimensions in MPD utilization, from technical aspects like data architecture and anonymized user data processing, to governance issues such as privacy, personal data protection regulations, and the crucial role of national regulations in facilitating cooperation between the public and private sectors. Speakers also emphasized that the use of MPD for official statistics can only be optimal if there is clear role definition, transparent mechanisms, and strong ethical principles.

Addressing Challenges and Building Capacity

Participants enthusiastically shared their views and questions regarding similar challenges in their own countries, such as technical capacity limitations, the absence of specific regulations, or communication gaps between NSOs and MNOs. These discussions served as a platform for exchanging ideas, fostering a shared understanding of the importance of building an inclusive, secure, and sustainable data ecosystem.

The training did not stop at a conceptual level. As a concrete step to strengthen technical capacity, participants from each country will be invited to attend a Short Course on MPD Processing and Analytics to be held in September 2025 in Bali. This intensive training program will equip participants with practical skills, ranging from cleaning and processing raw MPD data to visualization techniques and integration into national official statistical frameworks.

Real-World Implementation and Future Collaborations

To provide a direct overview of MPD implementation in government practice, the training concluded with field visits to two important locations: BPS-Statistics Indonesia and the Telkomsel Command Center. At BPS, participants observed firsthand how MPD data is processed and used to compile tourism and mobility statistics. At Telkomsel, participants received an in-depth explanation of data infrastructure, anonymous data aggregation methods, and data security and ethics procedures.

These visits served as cross-sectoral learning opportunities, reinforcing the importance of long-term partnerships between statistical agencies and cellular operators. From the government's side, technical understanding and adaptive policies are needed, while from the industry's side, a commitment to transparency, compliance, and openness is required to support national development goals.

Towards a Data-Driven Asia-Pacific

Through this series of training activities, it is hoped that collective awareness will be built across the Asia-Pacific region regarding the importance of transforming national statistical systems through the utilization of non-traditional data. MPD serves as a concrete example of how big data, initially used for commercial needs, can hold significant value in supporting data-driven development and public policy.

More than just a transfer of knowledge, this training serves as a foundational step for the formation of a strong, inclusive, and ethical cross-country and cross-sector collaborative ecosystem. With a spirit of sharing best practices and building trust, the Asia and Pacific region can collectively address data challenges in the digital era, moving towards official statistics that are more adaptive, responsive, and relevant to society.

Materials

Activity materials can be downloaded here:

Materials - Google Drive

Google Drive

Documentations

8 - 10 July 2025 | Jakarta, Indonesia

As part of the Regional Hub on Big Data and Data Science for Asia and the Pacific, this high-level workshop convenes decision-makers and strategic stakeholders to explore the transformative role of Mobile Positioning Data (MPD) in the production of official statistics. Participants will gain insight into the policy potential, governance considerations, and practical applications of MPD to drive data innovation across national statistical systems.

This three-day event includes expert-led panels, hands-on discussions, and strategic field visits to leading Indonesian institutions working with MPD. By highlighting successful case studies—including Indonesia’s use of MPD in tourism statistics—this workshop aims to stimulate regional collaboration, foster data-driven policymaking, and lay the foundation for long-term MPD integration.

Who Will Attend?

The workshop will be attended by senior managers from national statistics offices (NSOs), officials from tourism authorities, representatives from mobile network operators, and policymakers interested in big data governance from various country.

Objectives

This workshop is designed to empower policymakers and senior managers with strategic insights into the value and use of Mobile Positioning Data (MPD) in official statistics. Key objectives include:

• Introducing the foundational concepts and relevance of MPD for modern statistical systems.
• Showcasing real-world applications and success stories, with a focus on Southeast Asia.
• Promoting awareness and dialogue on data governance, privacy, and ethical data use.
• Enabling cross-sectoral collaboration among NSOs, tourism authorities, and telecom providers.
• Laying the groundwork for long-term adoption of MPD as a trusted data source for policymaking.

Program Outlines

Day One – 8 July 2025

Panel Session: Opportunity of Big Data and Data Science for Official Statistics

This opening session sets the stage by exploring the transformative impact of Big Data and data science on the evolution of official statistics. Participants will gain a comprehensive view of how national statistical systems can embrace innovation while upholding core values of accuracy, transparency, and public trust.

Panel Session: Big Data and Data Science for Decision Making

This session dives deeper into the role of data-driven decision making in public policy and governance. Experts will present case studies where Big Data—especially location-based data—has enhanced strategic planning, crisis response, and service delivery.

Day Two - 9 July 2025

Panel Session: MPD and Data Governance at Mobile Network Operator

This session provides an inside look at how mobile network operators manage Mobile Positioning Data, including the frameworks that ensure data security, privacy, and reliability. Speakers from leading telecom providers will explain how MPD is collected, stored, and shared under strict governance protocols.

Panel Session: The Administration and Budgeting in the Process of MPD Acquisition

This session focuses on the operational and budgetary aspects of acquiring and sustaining MPD initiatives. Speakers will discuss strategies for inter-agency coordination, licensing agreements, and long-term funding models to ensure scalable and sustainable MPD integration into national statistics systems.

Day Three - 10 July 2025

Visit to BPS–Statistics Indonesia

Participants will visit the Indonesian National Statistical Office, namely Badan Pusat Statistik (BPS) to observe firsthand how MPD is being integrated into Indonesia’s statistical workflows. The visit will highlight data integration practices, collaborative research initiatives, and visualization tools used to extract policy-relevant insights from MPD.

Visit to Telkomsel Command Center

The final visit offers a rare behind-the-scenes experience at one of Indonesia’s largest mobile network operators. Participants will tour Telkomsel’s data command center to understand the operational backbone of MPD generation.

Contact

For any questions relating to the knowledge development series, please contact us by email at bigdatahub@stis.ac.id.

Jakarta, Indonesia – The Machine Learning for Official Statistics workshop, held from February 3-7, 2025, successfully concluded in Jakarta, bringing together statisticians and data scientists from across the Asia-Pacific region. Organized by the Statistics Indonesia (BPS), United Nations Statistics Division (UNSD), and the Statistical Institute for Asia and the Pacific (SIAP), the workshop aimed to enhance statistical capabilities through machine learning techniques.

A Step Towards Modernized Official Statistics

With the increasing role of Big Data and Artificial Intelligence, the workshop provided a crucial platform for participants to explore machine learning applications in official statistics and Sustainable Development Goal (SDG) monitoring. Experts from BPS-Statistics Indonesia, UNSD, and SIAP guided the sessions, covering key topics such as:

• Fundamentals of data science and machine learning.
• Supervised and unsupervised classification methods.
• Advanced regression techniques and practical exercises using R.
• Tree-based models, including random forests and decision trees.
• Ethical considerations and bias identification in machine learning models.

Engaging Participants and Field Visits

The workshop was attended by 23 participants from National Statistical Offices (NSOs) across several Asia-Pacific countries, including Indonesia, Malaysia, Kazakhstan, Timor-Leste, Thailand, Türkiye, and Vietnam.

On the first day, all participants visited the Badan Pusat Statistik (BPS) headquarters in Pasar Baru, Jakarta, where they were warmly welcomed by Acting Deputy for Methodology and Statistical Information, Puji Ismartini, and her team. The visit began with a tour of the Integrated Statistics Center (PST), followed by a session at the BPS Command Center. After lunch, participants returned to Politeknik Statistika STIS to commence the training sessions.

Expert-Led Instruction and Practical Learning

The training was delivered by experienced mentors, including Christophe Bontemps from UNSIAP and Sean Lovell from UNSD. Participants explored essential concepts and definitions of data science and machine learning, classification methods, and regression techniques. In addition to theoretical material, the mentors provided interactive demonstrations and hands-on practice materials to facilitate better understanding. which can be accessed on

Alongside instructors from UNSIAP and UNSD, BPS experts also contributed to the sessions. Lya Hulliyyatus Suadaa, presented a case study on the classification of businesses at BPS, while Arie Wahyu Wijayanto discussed use cases of the Random Forest algorithm.

Strengthening Regional Collaboration

The event successfully fostered collaboration among national statistical offices, allowing attendees from various countries to share experiences and best practices. Discussions also focused on challenges in implementing machine learning models, particularly in accessing high-quality data and adapting models to varying institutional contexts.

Commitment to Future Innovation

As the workshop concluded, participants expressed a strong commitment to applying the knowledge gained within their respective statistical offices. Plans for further capacity-building initiatives and follow-up workshops were discussed to ensure continuous learning and innovation in the use of machine learning for official statistics.

The successful completion of this workshop marks a significant step forward in modernizing statistical systems through advanced data science and machine learning methodologies, paving the way for more data-driven decision-making across the Asia-Pacific region.

The world is experiencing a data revolution, and the ability to harness and interpret vast amounts of information has become a key driver of economic and social development. In the context of official statistics, the challenge lies in integrating traditional methods with cutting-edge technologies, such as machine learning (ML), to improve data quality, enhance decision-making processes, and ensure that statistical systems are responsive to evolving needs.

Official statistics are the backbone of public policy, informing decisions related to economic planning, social welfare, environmental sustainability, and governance. In the Asia-Pacific region, which is diverse in terms of its economies, cultures, and levels of technological development, the potential for machine learning to revolutionize the production, dissemination, and use of statistics is immense. However, there are significant challenges related to the accessibility of high-quality data, the development of appropriate ML models, and the capacity to adopt such technologies across varying institutional contexts.

This workshop aims to bring together statisticians and data scientists from the Asia-Pacific region to explore the application of machine learning techniques in the context of official statistics. The focus will be on enhancing the capacity of national statistical offices (NSOs) to integrate machine learning tools into their operations and improving the quality and timeliness of statistical outputs to support evidence-based decision-making that drives progress towards the SDGs.

Objectives

This workshop is organized by the Regional Hub on Big Data and Data Science for Asia and the Pacific, hosted by the Indonesian Government, in partnership with UNSD and UNSIAP. The specific objectives of this workshop include:

• Introducing the fundamental concepts and techniques of machine learning for improving official statistics, with a focus on SDG indicators.
• Developing technical skills for the utilization of machine learning to enhance official statistics and improve the monitoring of SDGs.
• Discussing opportunities for leveraging Machine Learning in participants' countries.Further information will be provided on the Regional Hub webpage as it becomes available: https://hub.bps.go.id/

Date and Venue

The workshop will take place over five days, from 3 to 7 February 2025, at the Politeknik Statistika STIS, Jakarta, Indonesia.

Please note that participants are responsible for booking their own accommodation.

The recommended nearby hotels include:

- Harper Hotel Cawang

- Best Western Cawang

Contact

For any questions relating to the workshop, please contact Ms. Lya Hulliyyatus Suadaa (lya@stis.ac.id).

Programme

The Statistics Indonesia (BPS), represented by Deputy Chief Statistician for Distribution and Services Statistics, Pudji Ismartini, attended the Ninth Session of the Committee on Statistics held in Bangkok from December 9 to 13, 2024. This event is part of the Asia-Pacific Statistics Week 2024, themed "Power of Data." The session consists of two segments: the senior officials segment on December 11 and the high-level segment on December 12 and 13.

In the high-level segment, representatives of member states discussed progress in implementing the "Declaration on Navigating Policy with Data to Leave No One Behind." Delegates also reflected on priority actions requiring resources, initiatives, and government engagement, as well as community participation, to ensure the achievement of the 2030 Agenda for Sustainable Development.

In the Senior Officials segment, delegates discussed key issues related to building an agile and responsive statistical system to address future challenges and highlighted priority issues in implementing the decisions made.

Through active participation in various agendas, Indonesia presented strategic initiatives such as Satu Data Indonesia, the use of new data sources to produce official statistics, and various statistical innovations to support the Sustainable Development Goals (SDGs). Indonesia also had the opportunity to showcase its statistical innovations and achievements through a dedicated booth at the exhibition event. This reflects Indonesia's commitment to improving the quality and relevance of data at both regional and global levels.

At the side event EXPERT GROUP: Unleashing the Power of Big Data in Official Statistics, BPS had the opportunity to share its country research and experiences from a collaborative project with ESCAP titled “The 2030 Data Decade – Strengthening the Institutional Capacity of National Statistical Offices in Asia and the Pacific to Use Innovative, New, and Big Data Sources for Official Statistics in Support of the 2030 Agenda for Sustainable Development.” On this occasion, BPS presented its experience in integrating big data, specifically Earth Observation data, to modernize the rice data collection process.

This session was held alongside the 20th session of the Governing Council of the Statistical Institute for Asia and the Pacific (December 9–10, 2024). Various expert group meetings and side events, including the 19th Management Seminar for Heads of National Statistical Offices, were organized to enrich and complement the committee's discussion activities.

Jakarta, December 5, 2024 – Regional Hub on Big Data and Data Science for Asia and The Pacific secretariat facilitated a strategic meeting with representatives from ESCAP, the UN Global Hub, and Experts, focusing on advancing the role of big data in regional agricultural monitoring and the achievement of Sustainable Development Goals (SDGs). The event took place in the Senate Meeting Room of the STIS campus, chaired by Prof. Setia Pramana.

The agenda included presentations on ongoing research initiatives, with notable contributions from Dr. Eng. Lya Hulliyyatus Suadaa on the UN Regional Big Data Hub and Prof. Setia Pramana on the institution’s data analytics research. These presentations showcased the alignment of big data applications with agricultural priorities and climate change mitigation.

Key discussions revolved around leveraging remote sensing technologies for rice growth monitoring. Prof. Huang Jingfeng highlighted the advanced methodologies used in China for detecting paddy growth phases using NDVI (Normalized Difference Vegetation Index) and stressed the need for high-resolution satellite imagery to cater to Indonesia’s continuous cropping cycles.

Meanwhile, Prof. Wayne Wobcke emphasized the potential of open-source platforms like Kaggle for methodological sharing. Eric Deeben the Chief Technical Advisor on the Big Data project underlined the importance of knowledge-sharing across hubs and ESCAP region. He further suggested that sharing of the One Rice project data with the global experts in secure and managed environment such as the regional hub can enhance  the project result and shorten the delivery timeline. A potential collaboration with Zhejiang University was also discussed, focusing on the implementation of AI and remote sensing in agricultural monitoring.

The meeting concluded with a commitment to advance the Mixed Method Project under the UN Regional Hub’s agenda. It was noted as a strategic initiative addressing the government’s priorities in rice production. Plans for knowledge-sharing webinars and partnerships to secure funding were also proposed.

BPS-Statistics Indonesia, in partnership with the Regional Hub on Big Data and Data Science for Asia and the Pacific, held a workshop titled “Utilizing Earth Observation Data for Rice Data Calculation” in Jakarta on December 3–4, 2024. The event brings together global experts as keynote speakers, with support from UN ESCAP and FAO.

This activity is a component of the "One Rice Data Initiative" project, aimed at developing the Mixed Method for rice production data calculation. The Mixed Method combines two approaches: field surveys and Earth Observation data. The use of big data in gathering field data is intended to enhance cost efficiency.

The purpose of this workshop is to enhance the skills of the human resources involved in the Mixed Method project, offering new perspectives on the use of high-resolution satellite imagery and modeling for crop types and yields. Through insights from global experts, participants will have the opportunity to learn from the experiences of other countries in implementing this technology.

The workshop covered four key themes: (1) Rice Mapping Using Optical and Microwave Satellite Data, (2) Rice Growth Monitoring and Yield Prediction, (3) The Philippine Rice Information System in Operation, and (4) High-Resolution Satellite Imagery Acquisition Using the COSMO-SkyMed Platform.

The keynote speakers for the workshop include:

1. Professor Jingfeng Huang, a distinguished scholar from Zhejiang University, renowned for his expertise in agricultural remote sensing with a particular focus on rice.
2. Jovino Lopez De Dios, Supervising Science Research Specialist from the Philippine Rice Research Institute (PhilRice) and head of the development of the Philippine Rice Information System.
3. Lorenzo De Simone, Geospatial Technical Adviser from FAO, who has been actively involved throughout 2024 in “The Big Data in Rice Mapping Project” in collaboration with BPS.
4. Dott. Vittorio Gentile, He has worked in e-GEOS and he is a member of Product Development and Innovation - Radar Application Unit in e-GEOS.
5. Dr. Jonathan Richetti,  a research scientist with the Spatial-Temporal Decisions team in CSIRO Agriculture & Food.

This workshop is a key component of an ongoing initiative aimed at enhancing rice data collection methods by integrating Earth Observation (EO) technology. The event serves as an important platform for fostering deeper collaboration between Statistics Indonesia (BPS) and global experts, with a shared focus on modernizing agricultural statistics. By leveraging big data—specifically satellite imagery. This initiative seeks to reduce reliance on traditional field surveys, while simultaneously addressing challenges such as high operational costs and limited field access, especially in remote areas. Through knowledge sharing and practical training, the workshop will enable participants to gain valuable insights into how big data and EO technology can be applied to improve agricultural monitoring systems, helping to inform more effective policy decisions for food security and agricultural sustainability.

Politeknik Statistika STIS and Regional Hub on Big Data and Data Science for Asia and The Pacific received a visit from a delegation from the Guangxi Zhuang Autonomous Region Bureau of Statistics and Guangxi University of Finance and Economics (12/08). The visit had an agenda to explore cooperation that could be established between the Guangxi government of China and Politeknik Statistika STIS and Regional Hub. Potential forms of cooperation include: lecturer and student exchange, research collaboration, and various other academic activities.

BPS has a Memorandum of Understanding with NBS China which allows for statistical cooperation between China and work units under the auspices of BPS.

During this visit, the Director of Politeknik Statistika STIS, Erni Tri Astuti, explained the study programs, research, activities and achievements that have been achieved by Politeknik Statistika STIS and Regional Hub, especially in the fields of statistics and big data.

It is hoped that this positive initiative can develop Politeknik Statistika STIS 's international relations in realizing Politeknik Statistika STIS as a World Class University.

Location: Remote (May - August 2024); Bangkok, Thailand (16-20 September 2024)

Background

The development of digitized economic activities increasingly supports buying and selling transactions without face-to-face interaction. Meanwhile, recommendations and reviews of goods offered digitally foster a trustworthy ecosystem, enabling consumers to confidently purchase products without needing to physically inspect them.

As digital commerce expands, the data generated from these transactions becomes a valuable resource. Price data from online markets, in particular, offers new opportunities for economic analysis and the calculation of Consumer Price Indices (CPI). However, accessing and utilizing this data requires specialized skills in web scraping and data analysis. This is where the ESCAP Big Data Project comes in, providing essential training to equip participants with the knowledge and tools to effectively gather, process, and analyze the online price data for CPI production.

The support will include a series of remote training sessions during May-August 2024, as well as an in-person workshop, to be held in Bangkok, Thailand, 16 - 20 September 2024. Following a series of online training webinars from May to August 2024, this workshop was organized to enhance the capacity of National Statistical Offices (NSOs) in Azerbaijan, Cambodia, Fiji, Lao PDR, Maldives, Nepal, Thailand, Tonga, Kiribati, and Uzbekistan in the area of web scraping techniques for Consumer Price Indices (CPI).

The Regional Hub on Big Data and Data Science for Asia and the Pacific supported this capacity development initiative by providing a team of mentors from Badan Pusat Statistik (BPS)- Statistics Indonesia. These experts played a pivotal role throughout the training program, both during the online sessions and in the in-person workshop. The BPS mentors co-facilitated the workshop alongside the lead facilitators, Frances Krsinich, Christophe Bontemps, and Ceri Regan, offering deep knowledge of web scraping, data processing, and CPI methodologies, thereby enriching the learning experience for all participants.

Objectives

The objectives of the programme are to develop skills to scrape price data from relevant websites and understand how it can be utilized to produce consumer price indices (CPI), including:

• To understand the extent and range of online price data, and to assess their usefulness for calculating the CPI.
• To understand the methodological considerations relating to the use of web scraped Prices for use in CPI calculations.
• To appreciate the ethical considerations prior to embarking on web scraping projects.
• To build skills and applications using Python, including the construction of web-scrapers using appropriate libraries and commands.
• To apply these tools and methods to websites relevant to produce national price indices and utilize the resulting data for consideration in CPI production.

Ongoing Mentorship Support

The mentorship program during the ESCAP Capacity Development Programme on Web Scraping for Price Statistics was supported by a diverse group of international experts. In addition to the four mentors from BPS Statistics Indonesia who attended the in-person workshop in Bangkok, the program also benefited from the contributions of online mentors: Cem Baş, (TÜİK at Turkey), Dominik Dabrowski(Stats Poland), Serge Goussev (Lead for Data Science and Engineering at Consumer Prices Division at Statistics Canada), and Luigi Palumbo (Researcher at Bank of Italy). These online mentors played a crucial role in the earlier phases of the training program, providing technical guidance and support to participants throughout the online training sessions held from May to September 2024.

Although these international mentors did not attend the in-person workshop in Bangkok, their expertise and involvement significantly enhanced the learning experience during the online phase, laying a strong foundation for the in-person sessions.

Activities During the Workshop

The workshop provided an intensive, hands-on learning environment, focusing on both theoretical and practical applications of web scraping. The key activities included:

• Python Coding and Web Scraping: Participants engaged in real-world examples of online scraping for prices datausing Python Programming Language, focusing on e-commerce websites in each nation. The BPS mentors provided direct support during these sessions, guidedparticipants through code development and troubleshooting.

• Automating Web Scraping Pipelines: A dedicated session focused on automating web scraping processes, which is essential for integrating web-based data into NSO workflows. BPS mentors led by example, sharing best practices on how automated pipelines have been implemented in Indonesia.

• Methodological Challenges and Solutions: Methodological sessions addressed common issues related to bias, representativity, and data quality when incorporating web-scraped data into CPI calculations.

Follow-up and Future Plans

During the closing session, Calvin, a representative of the Regional Hub on Big Data and Data Science and BPS - Statistics Indonesia, outlined the Hub’s commitment to supporting further development in this area:

1. Compiling Materials and Videos: The Regional Hub will compile and upload all workshop materials and recorded sessions onto its website, making these resources available not only to the participating countries but also to other countries in the Asia-Pacific region interested in learning from this content.

2. Ongoing Mentorship Support: The Regional Hub will continue providing technical mentorship through its team of experts from Indonesia. This support will be offered both virtually and, if requested, in person. Countries that wish to engage in further learning and capacity development can invite the mentors for on-site assistance under a self-funded arrangement. The Hub is committed to being a continuous source of guidance and knowledge sharing, ensuring that participating countries receive tailored support in implementing and expanding web scraping techniques for price statistics.

3. Future Initiatives: The Regional Hub plans to develop additional programs and resources to further enhance the capacity of NSOs in utilizing big data and innovative technologies for official statistics. These initiatives will be designed to meet the evolving needs of countries in the Asia-Pacific region and to support the broader objectives of the 2030 Agenda for Sustainable Development.

Outcomes and Achievements

The workshop achieved the following key outcomes:

• Participants improved their technical skills in using Python for web scraping and were able to apply these skills directly to websites that relevance to their respective NSOs.

• Automation processes for web scraping were better understood, laying the groundwork for integrating such processes into routine NSO operations.

• Provide insights to the participants to process web-scraped data towards CPI calculations, reducing reliance on traditional methods of data collection.

The four BPS mentors—Erma Purnatika Dewi (Directorate of Price Statistics), I Nyoman Setiawan (Directorate of Statistical Analysis and Development), Wahyu Calvin Frans Mariel and Muhammad Ghozy Al Haqqoni (Directorate of Statistical Information System)—were significant in the workshop's accomplishments, providing their practical experiences and expertise to assist participants in navigating the technical and methodological aspects of web scraping.

Participants and Mentors

Each participating country will also be assigned a mentor with experience of the use of web scraping who will be available to provide technical guidance and support.

Programme

From July 22 to July 26, 2024, BPS Statistics Indonesia, managed by the SSHI (Sistem Statistik Hayati Indonesia) team from the Directorate of Population and Employment Statistics, held the Capacity Building Event on Increasing the Use of Administrative Data Sources for Producing Official Statistics in Jakarta. This pivotal event aimed to strengthen Indonesia's National Statistical System (SSN) in support of Indonesia’s accession to the OECD. The workshop brought together a remarkable blend of national expertise and international support, ensuring a comprehensive learning experience for all participants.

The event was supported by the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP), United Nations Statistics Division (UNSD), and Statistics Norway. Notable figures from these organizations played key roles in the workshop, contributing their extensive knowledge and experience in administrative data and official statistics.

The training sessions were designed to equip participants with practical skills in utilizing administrative data for statistical purposes. The first three days featured general technical training, where participants from various ministries and institutions learned about the importance of integrating administrative data, This training included discussions on quality assurance frameworks, statistical legal framework, fundamental principles of official statistics, and other important discussion topics.

On July 25, a high-level meeting was held with senior officials from ministries and institutions managing administrative data. This meeting focused on strategic steps to enhance institutional governance and support the development of a vital statistics development. Key discussion is need of the involvement of all parties in strengthening regulations, including Presidential Regulations and related laws/regulations, to improve the provision of quality data that aligns with national interests. The regulations need to cover mechanisms, data governance, integration of microdata for statistical purposes, access arrangements, confidentiality and security of individual data, data dissemination, and compliance with OECD requirements.

The final day, July 26, was dedicated to a training workshop on Register-Based Census (RBC) for BPS staff. Participants explored the development and utilization of the Statistical Population Register (SPR), learning about the legal, technical, and operational requirements for transitioning to an RBC system. The training emphasized the significance of comprehensive civil registration systems and the integration of various administrative data sources.
Throughout the event, several important points were highlighted:

• Utilization of Administrative Data. The use of administrative data, such as birth and death registrations, is crucial for producing official statistics and developing a robust SSN. Initiatives like Satu Data Indonesia and the Generic Statistical Business Process Model (GSBPM) were emphasized for data integration and quality assurance.
• Collaboration Between Institutions. Effective collaboration between statistical offices and administrative data producers is essential for generating high-quality macro indicators and comprehensive analysis. This includes ensuring secure and structured microdata for national policy-making.
• Best Practices and International Standards. Participants learned from international experts about best practices in administrative data integration and the standards required for OECD membership. The importance of legal frameworks, stakeholder support, and political commitment was underscored.
• Challenges and Solutions. The training addressed various challenges in using administrative data, such as differences in definitions, classifications, and reference periods. Solutions like data linkage, record linkage, and the "Signs of Life" methodology were discussed to improve data quality and coverage.

The event successfully enhanced the skills and knowledge of Indonesian experts in utilizing administrative data for official statistics. This initiative is a crucial step towards modernizing Indonesia's SSN and achieving the high standards required for OECD membership. The workshop set a strong foundation for future advancements in data integration and statistical production, supporting Indonesia's vision of becoming a developed nation by 2045.

29 July - 2 August 2024

Jakarta, Indonesia

Background

The rapid development of Big Data technology provides opportunities for the modernization of business processes for statistical activities, including the potential use of Mobile Positioning Data (MPD) for official statistics. MPD is a form of big data generated by mobile network operators (MNOs) through tracking the location of mobile phones. MPD can be used for a wide range of purposes, including generating population and tourism statistics, measuring human mobility, creating data-driven solutions in urban planning, and establishing a response plan to disasters.

MPD consists of location data that is automatically stored by a mobile operator's system whenever a cell phone interacts with a cellular network, such as call activity, sending or receiving messages, and internet access. People's tendency to always carry mobile phones as an important item means that MPD can be used to study population movements in the dimensions of space and time more precisely. Therefore, the use of MPD has a great opportunity to improve data quality in official statistics. Indonesia is one of the countries that has already successfully utilized MPD in producing tourism statistics.

Objectives

This workshop is organized by the Regional Hub on Big Data and Data Science for Asia and the Pacific, hosted by the Indonesian Government, in partnership with ESCAP and Telkomsel. The specific objectives of this workshop include:

●      Increasing awareness of approaches to agreeing access to MPD and help equip participants to engage with national MNOs.

●      Developing technical skills for the processing of MPD for official statistics.

●      Developing technical skills in the analysis of MPD for official statistics.

●      Discussing opportunities for leveraging MPD in participants' countries.

The workshop is attended by participants from Kazakhstan, Bangladesh, Cambodia, Timor-Leste, Malaysia, and Indonesia, representing their respective national statistical offices and institutions involved in the advancement of official statistics through Big Data.

Programme

From July 2 to July 5, 2024, BPS Statistics Indonesia hosted the Data Cube Training, a pivotal event in the "One Rice Estimation" program. This workshop was an integral part of the "One Rice Estimation" program, which aims to revolutionize rice production data collection in Indonesia through the utilization of cutting-edge Earth Observation (EO) technologies. The initiative brought together a remarkable blend of local expertise and international support, ensuring a comprehensive learning experience for all participants. The workshop was supported by ESCAP and FAO, notable figures from these organizations, Eric Deeben and Dr. Lorenzo De Simone, played key roles in the workshop, contributing their extensive knowledge and experience in agricultural statistics and remote sensing technologies.

The workshop featured esteemed trainer Prof. Dr. Gilberto Câmara Neto, a Brazilian researcher renowned for his contributions to Geoinformatics, GIScience, Spatial Analysis, and Land Use Modelling. Prof. Câmara, a Senior Research Fellow at Brazil's National Institute for Space Research (INPE), is internationally celebrated for his efforts in promoting free access to geospatial data and his instrumental role in the satellite monitoring of the Brazilian Amazon rainforest.

The training sessions were designed to equip participants with practical skills in managing and analyzing Earth Observation (EO) data cubes. The first day introduced participants to the concepts of Satellite Image Time Series (SITS), emphasizing the importance of continuous crop growth monitoring. The hands-on training included setting up virtual machines on Microsoft Azure, configuring them, and installing SITS packages. This initial setup laid the foundation for participants to effectively handle and analyze large datasets.

On the second day, participants delved into the development of EO data cubes, learning about various satellite data sources such as Landsat, MODIS, Sentinel 1, and Sentinel 2. Techniques for data fusion and temporal stacking were covered, allowing participants to create comprehensive and temporally organized datasets. These sessions were crucial for understanding how to combine data from different satellites to analyze changes over time effectively.

The third day focused on training samples for SITS analysis. Participants explored methods for obtaining and validating training samples, employing techniques like clustering and Self-Organizing Maps (SOM) to measure the quality of these samples. The training also addressed the challenge of unbalanced training sample sets, introducing the Synthetic Minority Over-sampling Technique (SMOTE) to improve training sets.

On the final day, participants were introduced to various classification algorithms, including Random Forest, Dynamic Time Warping (DTW), and Deep Learning. Practical sessions on classifying EO data cubes and understanding the resulting probability cubes were conducted. Techniques for smoothing probability cubes and producing labeled classified maps were demonstrated, along with methods for assessing the accuracy of classification results to ensure reliability.

The Data Cube Training Workshop significantly enhanced the skills of Indonesian experts in EO data management and analysis, crucial for modernizing agricultural statistics. The training equipped participants with advanced methodologies for accurate rice production estimates, fostering better-informed food policies and enhanced food security in Indonesia. The event was a resounding success, setting a strong foundation for future advancements in agricultural data collection and analysis.

Imam Machdi, Deputy for Methodology and Statistical Information at BPS and currently acting as the Principal Secretary of BPS, delivered a speech at the Opening Ceremony of "The 8th International Conference on Big Data and Data Science for Official Statistics" in Bilbao, Spain, on June 10.

BPS played a significant role in this event, having established the Regional Hub on Big Data and Data Science for Asia and the Pacific in Jakarta in 2023. This positioning designates BPS as a center of excellence for using new data sources for official statistics. Attending the conference alongside Imam Machdi was Moh Edy Mahmud, Deputy for Balance Sheets and Statistical Analysis at BPS, and other BPS officials. Additionally, representatives from the Regional Hub Indonesia presented their past activities, plans, and challenges. They also had the opportunity to discuss and collaborate with other regional hubs and the UN Global Hub.

The conference was organized by BC3, in partnership with the United Nations Statistics Division, the Spanish Ministry of Foreign Affairs, the European Union and Cooperation, the Basque Government, the Spanish National Statistics Institute (INE), and the Basque Statistics Institute (EUSTAT). The overarching theme was "Informing Climate Change and Sustainable Development Policies with Integrated Data."

According to the official website, the conference originated from the need to address global challenges such as environmental issues, climate change, health crises, food insecurity, economic recovery, and human displacement. In a world with rapidly increasing data volumes, information often remains isolated within predefined scales and fields, rarely contributing to collective knowledge. The statistical, data science, geospatial, and modeling communities are tasked with delivering integrated knowledge to address these complex "wicked problems," which are intertwined, multi-stakeholder issues with solutions that may involve competing interests.

The conference aimed to share knowledge on emerging issues requiring the timely and flexible production of integrated scientific, statistical, and geospatial information. This involves collaboration with strategic partners from the public and private sectors, as well as academic and research institutes. A paradigm shift favoring open synthesis is needed to contribute to and reuse knowledge for decision-making. The event will feature a ministerial opening, high-level panels, technical sessions, and several workshops.

For more information, please visit: The 8th International Conference on Big Data and Data Science for Official Statistics, June 10-14, 2024, Bilbao, Spain

On March 22, 2024, we conducted a webinar on the Journey from MPD to Official Statistics. This webinar is organized by the Regional Hub on Big Data and Data Science for Asia and the Pacific, hosted by the Indonesian Government, in partnership with ESCAP.

The rapid development of Big Data technology provides opportunities for the modernization of business processes in statistical activities, including the potential use of Mobile Positioning Data (MPD) for official statistics. MPD is a form of big data which results from the high data volumes of mobile positioning by tracking the location of mobile phones. Mobile positioning data can be used for a wide range of purposes, including generating population and tourism statistics, measuring human mobility, creating data-driven solutions in urban planning, and establishing a response plan to disasters.

Indonesia is one of a few countries that are already using MPD for its official tourism statistics. Since 2016, BPS Statistics Indonesia has been using MPD for cross-border tourism statistics and has also been exploring other use cases. The extensive experience and lessons learned from Indonesia's journey in using MPD, can provide valuable insights for other National Statistical Offices (NSOs) seeking to adopt similar innovative approaches.

The specific objectives of this webinar include:

• Increasing awareness of the potential uses of MPD for official statistics.
• Sharing they journey of how MPD has been used for official statistics in Indonesia.
• Discussing opportunities for leveraging MPD in various statistical domains.

The opening remarks were delivered by Ms. Rikke Munk Hansen as Chief of Economic and Environmental Statistics of ESCAP and Mr Setia Pramana from Polytechnic of Statistics-STIS on behalf of the secretariat of Regional Hub on Big Data and Data Science for Asia and the Pacific. Webinar material was delivered by the experts from ITU as representatives of UN Task Team MPD, BPS Statistics Indonesia, and Telkomsel as one of MNO in Indonesia. This webinar was moderated by Alfatihah R.M.N.S.P. Munaf, BPS Statistics Indonesia. Table below shows us the detailed agenda.

This webinar was attended by 108 participants, including NSOs Maldives, Georgia, Uzbekistan, Kazakhstan, Malaysia, Gambia, Solomon Islands, Kiribati, New Zealand, Cambodia, Brunei, Republic of Armenia, Türkiye, United Arab Emirates, Timor-Leste, China, Pakistan, Sri Lanka, and Indonesia. There were also participants from representatives of MNOs, UNs, universities, private sectors, and other government agencies.

Documentation