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

L
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
2
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)
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)
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:
II.

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-informationsystems-msis-2014 (for Manila-only documents)
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)
b)
c)
d)
e)
f)
g)
h)
i)
identify pilot projects with a narrow scope;
generation of ideas on possible big data projects;
assist in understanding the legal framework especially with respect to multinational
corporations, e.g. ebay;
procedural and technical knowledge transfer;
organize webinar sessions on big data for interested NSOs;
organize a big data proof of concept for interested NSOs, e.g. organize a sprint;
capacity building;
sharing of best practices (taking into consideration socio-economic factors); and
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, subjectmatter 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
5
b)
c)
d)
should engage in fact finding, research, and case studies. The final outcome of such
committee is a framework for the use of big data.
The framework should be presented to the management to gain their interest in the
project and seek approval.
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.
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.
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As a result, the experts drafted a short-term list of actions for a SDMX working group:
a)
b)
c)
d)
e)
contribute with information on how to start implementation of SDMX (taking care not to
duplicate the information already available);
work on advocacy materials to attract the interest of management and explain what is
SDMX in simple terms;
work on a pilot to demonstrate the use of SDMX, e.g. devinfo;
work on a questionnaire on the usage of SMDX in Asia-Pacific; and
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
9
 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
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Introduction to Topic (ii): Standards-based modernization
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, BPSStatistics 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
END OF MEETING
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Topic (iii): General discussion and conclusions
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 DirectorGeneral 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
----------UNITED NATIONS SECRETARIAT
UNITED NATIONS STATISTICS DIVISION
Mr Abdulla Gozalov, Chief, Global Data Services Unit, New York
----------UNITED NATIONS BODY
UNITED NATIONS GLOBAL PULSE
Mr Quaggiotto Giulio, Pulse Lab Manager, Jakarta
----------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
----------SECRETARIAT
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Ms Zeynep Orhun Girard
Statistician, Economic and Environment Statistics Section
(EES), SD
Mr Marko Javorsek
Associate Statistician, EES, SD
___________________
17