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UNITED NATIONS ECONOMIC AND SOCIAL COMMISSION FOR ASIA AND THE PACIFIC (ESCAP)

Expert Group Meeting

Joint UNECE/Eurostat/OECD/ESCAP/ADB Meeting on the

Management of Statistical Information Systems (MSIS 2014)

Dublin, Ireland and Manila, Philippines, 14-16 April 2014

Report for Manila, Philippines

I. Background and organization of the meeting

1. The meeting on Management of Statistical Information Systems (MSIS 2014), jointly organized

by the United Nations Economic Commission for Europe (UNECE), the Organisation for Economic

Cooperation and Development (OECD), the Statistical Office of the European Union (Eurostat), the

United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) and the Asian

Development Bank (ADB), was held in Dublin, Ireland, hosted by the Central Statistics Office of Ireland

and Manila, Philippines, hosted by the ADB, from 14 to 16 April 2014. The two geographical locations

of the meeting were linked through videoconference during afternoon sessions in Manila. The

objective of the MSIS meeting was to create awareness of research, standards and tools related to

modernization of statistical production and services and share experiences of related developments

in national statistical systems and international organizations.

2. This expert group meeting is part of implementing recommendation of the ESCAP Committee

on Statistics second session1 and decision from its third session,2 under the area of work on

modernization of statistical production and services.

3. MSIS has been organized annually by UNECE, Eurostat and OECD since 2000. Since 2013 ESCAP

joined the organizing committee. MSIS 2013 was hence organized in two locations (Paris and

Bangkok), with joint sessions held during morning hours in Paris and afternoon hours in Bangkok,

using a web-link. The same modality was replicated for MSIS 2014.

4. Thirty-three experts from 18 countries and five international organizations attended MSIS 2014

in Manila. The meeting was intended for IT managers from statistical organizations and other

specialists responsible for the coordination, planning and management of complex projects in

statistical information processing. The participation at MSIS 2014 differed from that in the previous

year.

1 E/ESCAP/CST(2)/9: Recommandation 2/1 (http://www.un.org/ga/search/view_doc.asp?symbol=E/ESCAP/CST(2)/9&Lang=E)

2 E/ESCAP/CST(3)/17: Decision 3/5 (http://www.un.org/ga/search/view_doc.asp?symbol=E/ESCAP/CST(3)/17&Lang=E)

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5. The discussions took place in plenary and in smaller groups, and were informed by

presentations from the participating experts and the secretariat on topics such as the use of big data

for official statistics, standards-based modernization of official statistics, and the role of IT in

organizational change. The programme and list of participants for the event are included as Annex I

and II, respectively.

6. The discussions resulted in a number of conclusions and recommendations pertaining to future

collaboration in the Asia-Pacific region on the use of big data for official statistics and the

modernization of statistical production and services, which are presented below.

7. MSIS 2014 documents, papers and presentations are available at:

http://www.unece.org/stats/documents/2014.04.msis.html (for joint session documents

and Dublin-only documents)

http://www.unescap.org/events/joint-meeting-management-statistical-information-

systems-msis-2014 (for Manila-only documents)

II. Main conclusions

8. The participants stressed that the work on modernization of statistical production and services

is not an area that one country can master alone, and that intensified regional collaboration would

be hugely beneficial.

9. The experts noted that the Strategic Advisory Body for the Modernization of statistical

production and services in Asia and the Pacific (SAB-AP) is tasked to drive and support changes

towards the modernization of statistical production and services in the Asia-Pacific region, but is less

active at the moment. It is important for the regional advisory body to be active and engaged, as well

as to support experts' involvement in regional collaboration. Thus, the expert group called on the

heads of NSOs in the region to actively engage in the work of SAB-AP.

10. The preferred mode of regional collaboration suggested by the experts was to work in smaller,

focused and technical working groups on clearly identified priority areas. The working groups would

need to be active in order to attract the commitment of participants. Experts from any country or

international organization are welcome to join such regional collaboration working groups at any

point in time, as long as they have the commitment and motivation necessary.

11. The expert group expressed interest to work at the regional level on the following priority

areas: big data, SDMX, e-collection, data dissemination and visualization. These areas are mostly in

line with the priority areas identified at MSIS 2013 with the exception of GSBPM and institutional

issues which were also put forth in 2013.

12. It was suggested that working groups should be formalized, because it would facilitate the

approval process in the NSOs for experts to be actively involved and bring continuity to the work. The

groups should have clear reporting lines and receive strategic direction from the SAB-AP.

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13. In order for experts participating in working groups to stay motivated and committed, priority

must given by NSOs management to this area of work. This, in turn, may be due to limited resources

available, especially human and financial resources. It was stressed that management needs to

support experts' participation in regional collaboration efforts, by allocating staff time and, if possible,

also some financial resources (e.g. travel).

14. The participants acknowledged that it is important to keep experts motivated to work on

collaborative efforts for the modernization of statistical production and services. In that regard it was

suggested that periodic virtual meetings be organized, where experts would report progress and

short and long-term plans be agreed. Subject to availability of funds, physical meetings could be

organized, potentially back-to-back with other events to save time and cost.

15. The participants put forward the following potential modalities for regional collaboration:

a) conducting virtual expert group meetings (video conference);

b) establishing experience and data sharing platforms and discussion forums;

c) facilitating bilateral partnerships through study/exchange visits and in-country technical

assistance;

d) facilitating collaboration with more advanced systems in Europe that have many

experiences in these fields;

e) establishing links to other subregional organizations (e.g. ASEAN, SPC, SAARC), using

these forums for advocating for the priorities identified and for getting support from

heads of NSOs as well as finding linkages to their work programmes; and

f) organizing focused and technical workshops on the priority issues.

16. It was put forward that regional and international organizations were best placed to

coordinate and facilitate the establishment and the work of these groups, because they have close

links to NSOs in the region and an overview of ongoing regional and global efforts. International

organizations are well placed to facilitate the advocacy vis-à-vis heads of NSOs and other parts of the

NSS, needed to support this line of work in the region, in addition to providing and coordinating

technical cooperation activities, organizing training, facilitating sharing of knowledge, tools and

systems, and facilitating collaboration, partnerships and communication.

III. Summary of the break-out group discussions

17. The discussions focused on big data on the second day of the meeting; and on the possible

ways forward for regional cooperation on the third day. Participants broke into three groups on the

big data discussion and in two groups on the way forward discussion.

A. Break-out group discussions on big data for official statistics

18. During the focused discussion on the use of big data for official statistics the participants put

forward a number of ideas for regional collaboration for big data use:

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a) identify pilot projects with a narrow scope;

b) generation of ideas on possible big data projects;

c) assist in understanding the legal framework especially with respect to multinational

corporations, e.g. ebay;

d) procedural and technical knowledge transfer;

e) organize webinar sessions on big data for interested NSOs;

f) organize a big data proof of concept for interested NSOs, e.g. organize a sprint;

g) capacity building;

h) sharing of best practices (taking into consideration socio-economic factors); and

i) providing and sharing of guidance on private-public cooperation.

19. The expert group identified the following advantages of big data: reduced time for data

collection and processing; help in improving accuracy by collecting data from large enterprises, e.g.

from big supermarket chains; use for data confrontation. The main challenges that were identified by

the group were: lack of understanding what big data is – no clear definition of big data; lack of

resources to take full advantage of big data; the use of big data depends on the level of development

of the country and on the issue at hand; lack of capacity in NSOs for data mining of these data

sources; the lack of metadata on big data; difficulties in generating new ideas; convincing statisticians

of accuracy is a challenge for IT experts in the absence of underlying algorithms; legal issues regarding

privacy and data protection; and identification of mandate to use big data.

20. The experts noted that there is a need for the NSOs to start using big data and the importance

of partnerships with private sector and academia. NSOs should look into signing MoUs with owners

and producers of big data, as well as with academics to develop techniques for data analysis. Among

the resources needed for the use of big data, having adequate budget was identified as the most

important together with qualified human resources (data experts, IT experts and subject-matter

experts) and technology infrastructure. The need for training and more general information about big

data sources was also expressed.

External perspectives on the use of big data for official statistics

21. The first two break-out groups discussed the external perspectives of the use of big data for

official statistics. They discussed what kinds of partnerships are needed between national statistical

institutions and private sector as producer/owner of big data sources.

22. The experts highlighted that the partnerships between NSOs and the private sector are

important to get the access to data sources owned and produced by these companies. The

accessibility and storage of the data sets will need to be defined. The NSOs will also need to

understand the data structures of these big data sets and the methodologies for analysis of big data.

The experts also think that the NSOs will also need the technical expertise from private companies.

23. It is important to identify benefits for the private sector to develop arguments that NSOs could

use to convince private sector companies to share their big data sets with the NSOs. The participants

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pointed out benefits, such as media exposure (publicity) for companies, data philanthropy,

benchmarking, and development of human resources. Furthermore, there is a need to educate the

private sector and government agencies in order to broker the arrangements for big data

exchange/use.

24. Participants reviewed the following good practices for engagement with private sector

companies to provide big data sources to NSOs:

a) The legal agreements in China depend on the company that the NBS works with, but

most analysis is done by the company and aggregate data is provided to the NBS. In

China big data from companies is used as a supplement to official statistics.

b) The strength of legislation is key for soliciting data from the private sector. For instance,

in the case of Australia, the statistical legislation allows ABS to get data that is necessary

for official statistics whereas other countries such as Cambodia or Malaysia face

difficulties in collecting data from the private sector.

c) In the case of Republic of Korea, the Bank of Korea (BOK) established a strategic alliance

with a private company to provide pro-bono text data (mainly newspaper texts) to the

BOK. This project brings benefits to both parties. On one hand, it allows BOK to conduct

a text-mining pilot project without any budget implications, and on the other hand, it

provides access to text data analysis methodologies and potential to find new business

opportunities to the private company.

25. Some experts felt that it is difficult for the NSOs to generate new ideas of how to use big data

for official statistics. Thus, several concrete examples were identified:

a) national policy for forecasting inflation;

b) KOSTAT’s example of using the Billion Price Project (BBP) to construct daily price

movements;

c) satellite imaging; and

d) civil registration in India: establishing a system to connect private and public hospitals

records databases.

Institutional changes needed for the use of big data for official statistics

26. The third break-out group discussed the internal organisation of NSOs to exploit big data. What

institutional changes in the NSO are needed for the use of big data sources in the production of

official statistics (capacity/training, advocacy, organisational structure, etc.).

27. The experts discussed what is needed internally in the NSO to take the advantage of big data

and proposed steps the NSO could take to pursue a concrete idea for using big data for official

statistics:

a) Technical committee should be set up, consisting of users, data producers, subject-

matter experts, and IT experts. The task of the committee is to explore the potential of

such project or data source and the technical aspects of such project. The committee

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should engage in fact finding, research, and case studies. The final outcome of such

committee is a framework for the use of big data.

b) The framework should be presented to the management to gain their interest in the

project and seek approval.

c) Once the framework is approved the participants suggest beginning with a pilot project.

It is important to start the project and try the viability with concrete examples.

d) After the viability of the big data project (or data source) is established, external

consultations and advocacy will be needed. The experts agreed that the users will need

to be educated about the project and its benefits.

28. The participants also suggested that cultural or behavioural changes will be required to take

the full benefit of big data. Internally, the NSOs and other government agencies will need to go

through a ‘cultural change’ to become more comfortable with new sources of information. They will

need to engage in a dialogue with the private sector and establish partnerships. External changes will

also be needed; such changes will need to happen with the legal framework, addressing privacy

issues and enabling access to data.

B. Break-out group discussions on the possible ways forward for regional cooperation in

supporting the modernization of statistical production and services

29. Participants broke into two break-out groups to discuss two topics identified as regional

priorities: SDMX and e-collection/dissemination. A third group to work on GSBPM was also proposed

by the secretariat, but there was no interest among the participants for that topic.

Break out group discussion on SDMX

30. The following main issues for regional work on SDMX were mentioned by the experts: need for

advocacy to attract high-level attention; need for clarification of which division within NSO and which

agency within NSS is responsible for SDMX implantation; need to define collaboration on SDMX

implementation between divisions within NSOs and with other agencies within NSSs; need for

documentation and information in national language; need for demonstrating the benefit of SDMX

(mainly on national level for exchange of data between government agencies); need to obtain

approvals to participate in regional collaboration projects.

31. Based on the issues identified, the participants recommended that regional collaboration

efforts on SDMX should focus on the following areas: how to obtain interest of management; draft a

guide about what needs to be known to start with SDMX implementation; organization of study visits

and on the job training exchanges between countries; finding ways to use SDMX for dissemination

and development of dissemination DSDs; and working on a proof of concept / practical

demonstration. Due to the unavailability of funds it was recommended for the regional collaboration

group on SDMX to begin work with virtual meetings.

32. As a result, the experts drafted a short-term list of actions for a SDMX working group:

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a) contribute with information on how to start implementation of SDMX (taking care not to

duplicate the information already available);

b) work on advocacy materials to attract the interest of management and explain what is

SDMX in simple terms;

c) work on a pilot to demonstrate the use of SDMX, e.g. devinfo;

d) work on a questionnaire on the usage of SMDX in Asia-Pacific; and

e) contribute to a knowledge exchange platform with materials.

33. The following elements were identified to be useful for advocacy within statistical organizations

to obtain management interest in SDMX:

a) show existing implementations, e.g. country data, IMF SDDS+;

b) show how SDMX fits in with other corporate processes, or as part of other IT solutions;

c) promote SDMX as an open standard initiative;

d) use the MSIS report.

Break-out group discussions on e-collection and data dissemination

34. Experts in this group identified the scope for e-collection as an issue since it can cover a range

of topics such as: computer assisted collection, internet/telephone interviewing, crawling, Big data,

etc. Assessing the quality of e-collected data and ensuring security and privacy of data and

respondents in e-collection settings were identified as topics for regional collaboration.

35. Experts pointed out the following issues for regional collaboration on dissemination: data

visualization; micro-data dissemination; ICT for dissemination; and open data policy.

IV. Summary of the plenary discussion on big data

36. A number of experts saw the need to use big data for official statistics; however, for many

participants it was not clear how they can use big data in their organizations. The concrete benefits of

big data are not understood yet, as the projects form some NSOs show. Moreover, to assess quality of

big data sources it is important to scrutinize the methodologies, e.g. modelling of algorithms behind

internet searches.

37. The participants pointed out several issues with the use of big data for official statistics and

come from some limits of big data, such as representativeness and selection bias, which can be more

severe than sampling bias. By using big data one gets into the trap of causality or correlation, and so

it is hard to assess what is the explanatory power of the statistical outputs based on big data and

what are we exactly measuring. Patterns are not equal to statistical inference and users need to

understand related quality issues. This is particularly important given that a major benefit of using big

data is the option of improving the timeliness of statistics. Additionally, by using big data there is also

the possibility of producing new statistical information that is traditionally not produced by the NSO

or other agencies in the NSS.

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38. Participants noted that the use of big data for official statistics will be a long process. At least in

the short-term, statistics produced using big data will not replace traditional ways of producing

statistics; traditional indicators (e.g. CPI) are there to stay. New measures, constructed using big data,

are likely to supplement the plethora of available information for policy-makers. However, there are

other uses for big data, such as data confrontation, or in other words comparison between official

statistics and statistics produced using big data. The use of big data for data confrontation can serve

to improve the quality of official statistics and challenge the agencies producing them.

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V. Annex I: Meeting agenda

Agenda for Manila

Monday, 14 April

Manila-only session 10:30 – 11:30 Opening and welcoming remarks Agenda and functioning of the meeting Self-introductions by participants 11:30 – 11.45 Coffee break & Group photo 11:45 – 12:30 Modernization of statistical production and services Global and regional perspectives

12:30 – 14:00 Lunch break

14:00 – 15.30 Big Data (i): Official statistics and the use of non-traditional data sources Giulio Quaggiotto, UN Global Pulse, Pulse Lab Jakarta 15:30 – 16.00 Coffee break (Preparation and testing of video-link with Dublin) Joint Manila-Dublin session 16.00 – 16.10 Opening of the meeting and adoption of the agenda 16.10 – 16.25 Keynote address – Padraig Dalton, Director General, Central Statistics Office,

Ireland 16.25 – 17.30 Introduction to Topic (i): How IT can contribute to changing organizational culture Discussants: Joe Treacy, Central Statistics Office, Ireland, Joseph Parsons, National

Agricultural Statistics Service, U.S. Department of Agriculture and Christine Wirtz, Eurostat

A Case Study - How IT is Contributing to Changing the ABS Culture – Patrick Hadley, Australia

Information Technology Centralization and Modernization Efforts and the Impact on Organizational Culture at a Federal Statistical Agency – Joseph L. Parsons, USA/NASS

Streamline, standardize and automate statistical data processing – An IMF case study – Andreas Hake, IMF

17.30 – 18.00 Coffee break 18.00 – 19.00 Topic (i): Continued

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Is IT rationalisation a way to change service culture? – Pál Jancsók, Eurostat

Factors influencing open source software adoption in public sector national and international statistical organizations – Brian Buffet, UNESCO Institute for Statistics

The ICT Change Management at Istat – Silvia Losco, Italy

OECD.Graph solution - enhancing the graphics production process – Susan Cartwright, OECD

19.00 – 19.30 Topic (i): General discussion and conclusions

Tuesday, 15 April

Manila-only session 10:30 – 11:45 Big Data (ii): paper presentations

Big Data and Official Statistics in China – Liang Damin and Cheng Jinjing, National Bureau of Statistics of China

Big Data and Official Statistics: Analysis of Recent Discussions in Statistical Communities – Takao Itou, Ministry of Internal Affairs and Communications, Japan

Challenges, Opportunities and Issues on Using Big Data for Meeting Current and Emerging Demands on Measuring Progress and Development – Jose Ramon G. Albert, Philippine Institute for Development Studies

A practice to produce online price index based on BPP (Billion Price Project) – Jung-Im Ahn, Statistics Korea (KOSTAT), Republic of Korea

Questions & answers 11:45 – 12:00 Coffee break 12:00 – 13:00 Big Data (iii): Group discussions

13:00 – 14:30 Lunch break

14:30 – 15:00 Big Data (iii): Wrap-up of group work and presentation preparation 15:00 – 15.45 Big Data (iii): Group work presentation and plenary discussion 15:45 – 16.00 Coffee break Joint Manila-Dublin session 16.00 – 17.05 Introduction to Topic (ii): Standards-based modernization

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Discussants: Trevor Fletcher, OECD, Eric Hermouet and Marko Javorsek, ESCAP

Statistical Metadata Driven eForms – Improved Business Efficiency through Standardised Automated Statistical Processes – Oleg Volguine, Australia

Capturing Metadata Objects in Statistical Business Processes and Using them to Monitor the Process – Deniz Özkan and Güneş İnan Vıcıl, Turkey

Meeting today’s dissemination challenges – Implementing international standards in.Stat – Jonathan Challener, OECD

European Census Hub: A Cooperation Model For Dissemination of EU Statistics – Christine Wirtz, Eurostat

17.05 – 17.20 Questions 17.20 – 17.50 Coffee break 17.50 – 18.35 Topic (ii): Continued

ADB/ESCAP Implementation of global SDMX Data Structure Definitions (DSDs): A pilot project in Asia and the Pacific – Denis Ward and Artur Andrysiak, ADB

SDMX Implementation Via DevInfo 7.0 in Ghana Community Systems Foundation – Chris Dickey, DevInfo

GSBPM and GSIM in Statistics Norway – Rune Gløersen, Norway 18.35 – 19.15 Topic (ii): General discussion and conclusions

Wednesday, 16 April

Manila-only session 10:30 – 11:45 Parallel sessions

(1) Standards supporting the modernization of official statistics: system-wide implementation

How IT can contribute to changing organizational culture – Reenesh Latchman, Fiji Bureau of Statistics

Toward the Modernization of Official Statistics in BPS-Statistics Indonesia: Standardization Initiatives and Future Direction – Said Mirza Pahlevi, BPS-Statistics Indonesia

The creation and implementation of an information system «Metadata» – Anar Akhambayeva, Agency of Republic of Kazakhstan on Statistics

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Statistical procedure of Thailand developed by the Generic Statistical Business Process Model (GSBPM) version 4.0 – Tanes Komolvipart, National Statistical Office, Thailand

Building Statistics Hub and Intranet/Dissemination Portal – Nguyen Thi Thu Hong, General Statistics Office of Viet Nam

Questions & answers

(2) Standards supporting the modernization of official statistics:

application specific implementation

Management of Statistical Information in Socio-Economic and Caste Census – Purnendu Kishore Banerjee, Office of the Registrar General and Census Commissioner, India

Tablet PC usage for statistical data collection – Lkhagva Myagmarsuren, National Statistical Office of Mongolia

IT contribution for the Population and Housing Census 2011 in Sri Lanka – Buddhika Wickramasinghe, Department of Census Statistics, Sri Lanka

CountryData: Using SDMX to exchange MDG data between national statistical offices and international agencies – Abdulla Gozalov, United Nations Statistics Division

Questions & answers 11:45 – 12.00 Coffee break 12:00 – 13:00 The way forward for regional cooperation in modernization of statistical

production and services (i): Working groups

13:00 – 14:30 Lunch break

14:30 – 15:00 The way ahead for regional cooperation in modernization of statistical

production and services (ii): Wrap-up of group work and presentation preparation 15:00 – 15.45 The way ahead for regional cooperation in modernization of statistical

production and services (iii): Group work presentation and plenary discussion 15:45 – 16.00 Coffee break Joint Manila-Dublin session 16.00 – 17.20 Introduction to Topic (iii): Innovation Discussants: Marton Vucsan (Statistics Netherlands) and Carlo Vaccari (Istat, Italy)

On the use of internet robots for official statistics – Olav ten Bosch and Dick Windmeijer, Netherlands

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Big Data use cases and implementation pilots at the OECD – Jens Dosse, OECD

Implementation of GIS technology to support Population Census operations in Albania – Nexhmije Leçini, Albania

Dealing with Big Data for Official Statistics: IT Issues – Monica Scannapieco, Italy

Quality Assurance – Population and Housing Census 2011 – Alma Kondi, Albania

17.20 – 17.40 Coffee break 17.40 – 18.40 Topic (iii): Continued

The Implementation of E-survey in the Department of Statistics Malaysia – Habsah Salleh, Malaysia

Data Management and Dissemination for Censuses and Surveys at National Institute of Statistics – Kimhor Meng, Cambodia

Open Data Initiative of Government of India – Fostering Innovations, Creating Opportunities – Shri B.N. Satpathy, India

Informing a Data Revolution Project – Trevor Fletcher, Paris21 18.40 – 19.20 Topic (iii): General discussion and conclusions END OF MEETING

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VI. Annex II: List of participants

MEMBERS

AUSTRALIA

Mr Oleg Volguine, Assistant Director, Technology Application Delivery Branch, Technology Services Division, Australian Bureau of Statistics, Sydney, Australia

CAMBODIA

Ms Hang Lina, Director-General, National Institute of Statistics, Ministry of Planning, Phnom Penh

Mr Kimhor Meng, Deputy Director-General, National Institute of Statistics, Ministry of Planning, Phnom Penh

CHINA

Mr Liang Da Min, Director, Data Management Center, National Bureau of Statistics of China, Beijing

Ms Cheng Jinjing, Deputy Director, Department of Statistical Design and Management, National Bureau of Statistics of China, Beijing

FIJI

Mr Reenesh Latchman, Information and Dissemination Division, Fiji Bureau of Statistics, Suva

INDIA

Mr Purnendu Banerjee, Deputy Registrar General, Census Division, Office of the Registrar General & Census Commissioner, New Delhi

INDONESIA

Mr Said Mirza Pahlevi, Head, Database Development Sub Directorate, Statistics Indonesia - BPS, Jakarta

JAPAN

Mr Takao Itou, Executive Statistician for International Statistical Affairs, Office of Director- General for Policy Planning (Statistical Standards), Ministry of Internal Affairs and Communications, Tokyo

KAZAKHSTAN

Ms Anar Akhambayeva, Head, Coordination of Metadata Division, Agency on Statistics of the Republic of Kazakhstan, Astana

KYRGYZSTAN

Ms Nursuluu Tazhibaeva, Specialist, National Statistical Committee of the Kyrgyz Republic,

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Bishkek

MALAYSIA

Ms Habsah Salleh, Director, Data Coordination Division, Department of Statistics Malaysia, Putrajaya, Malaysia

Ms Rosnah Muhammad Ali, Statistician, Department of Statistics Malaysia, Putrajaya, Malaysia

MONGOLIA

Mr Lkhagva Myagmarsuren, Director, Data Processing and Technology Department, National Statistical Office of Mongolia, Ulaanbaatar

NEPAL

Mr Suman Raj Aryal, Deputy Director General, Central Bureau of Statistics, Kathmandu

PHILIPPINES

Mr Edwin Aragon, Information Systems Analyst III, Information Management and Communication Division, Philippine Statistics Authority, Makati City, Philippines

Mr Jose Ramon G. Albert, Senior Research Fellow, Philippine Institute for Development Studies (PIDS), Makati City, Philippines

REPUBLIC OF KOREA

Ms Ri Yu, Deputy Manager, Monetary Policy Information Systems Team, Information Technology Department, Bank of Korea, Seoul

Ms Jung-Im Anh, Director General, Informatics and Services Bureau, Statistics Korea (KOSTAT), Daejeon, Republic of Korea

Mr Kibong Park, Deputy Director, ISurvey Management Division, Informatics and Service Bureau, Statistics Korea (KOSTAT), Daejeon, Republic of Korea

SRI LANKA

Mr Buddhika Wickramasinghe, Assistant Director (ICT), Department of Census & Statistics, Colombo

THAILAND

Mr Tanes Komolvipart, Senior Professional Computer Technical Officer, National Statistical Office, Bangkok

Mr Wichit Piyawattanakul, National Statistical Office, Bangkok

VANUATU

Mr Rara Soro, ICI Manager, Vanuatu National Statistics, Port Vila

VIET NAM

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Ms Nguyen Thi Thu Hong, Chief, Planning and Training Division, Center of Statistical Information System I (COSIS I), General Statistics Office, Hanoi

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UNITED NATIONS SECRETARIAT

UNITED NATIONS STATISTICS DIVISION

Mr Abdulla Gozalov, Chief, Global Data Services Unit, New York

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UNITED NATIONS BODY

UNITED NATIONS GLOBAL PULSE

Mr Quaggiotto Giulio, Pulse Lab Manager, Jakarta

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INTERGOVERNMENTAL ORGANIZATION

ASIAN DEVELOPMENT BANK (ADB)

Mr Artur Andrysiak, Statistician, Development Indicators and Policy Research Division, Economics and Research Department, Manila

Mr Danis Ward, Consultant, Development Indicators and Policy Research Division, Economics and Research Department, Manila

Mr Douglas Brooks, Director, Development Indicators and Policy Research Division, Economics and Research Department, Manila

ESCAP REGIONAL INSTITUTION

STATISTICAL INSTITUTE FOR ASIA AND THE PACIFIC (SIAP)

Mr Hiroyuki Kitada Deputy Director, Chiba, Japan

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SECRETARIAT

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Ms Zeynep Orhun Girard Statistician, Economic and Environment Statistics Section (EES), SD

Mr Marko Javorsek Associate Statistician, EES, SD

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