The document summarizes a workshop on writing metadata for development indicators held in Lusaka, Zambia in July-August 2012. The workshop aimed to build capacity for writing metadata to improve data quality and resolve discrepancies between sources. It discussed challenges in metadata management within and outside national statistical organizations. The workshop sought to provide tools and guidance on customizing MDG metadata and implementing standards like SDMX. Participants hoped to narrow gaps between data sources and resolve international and national discrepancies.

1. Summary of
workshop
Workshop on Writing Metadata for
Development Indicators
Lusaka, Zambia
30 July – 1 August 2012

2. Workshop objective
• Build capacity of countries in writing metadata
for development indicators
• with a view to improving data quality
• and resolve discrepancies between national and
international sources

5. Source: International Labour Organization (ILO), Guide to the new Millennium Development Goals Employment Indicators
including the full set of Decent Work Indicators, 2009.

6. UNDP Guide to Measuring
Human Development
“… a reference tool
that provides
guidance on
statistical
principles…”

7. Types of metadata

8. Uses of metadata
• Data discovery
• Define and describe data resources
• Drive statistical production
• Capture information about sources
• Integral to the IT environment
• Describe quality of outputs
Source: Graeme Oakley, Australian Bureau of Statistics
www.unescap.org/stat/apex/2/APEX2_S.4_conference_Statistical%20Metadata%20Standards.pdf

9. Existing guidance

10. Metadata and development indicators
• indicators often have multiple data sources
• users may have limited knowledge of statistics
• discrepancies in MDG estimates

11. Improving MDG metadata is a global priority
‘National statistical systems to
improve the compilation of metadata
in countries and their accessibility by
users’
Recommendation from the
International Conference on MDGs Statistics, Manila, October 2011

12. Challenges you face
Within the NSO
• Need a metadata champion
• Lack of consistent practices
• Lack of awareness about metadata
• Capacity gaps in metadata management
• Limited documentation on business processes
• Not mandatory to produce metadata
• Data influenced by operating partners
• Limited legislation / accountability
• Reluctance to share knowledge
• Lack of dissemination policies and systems

13. Challenges you face
Outside the NSO
• Other organizations require training
• Limited resources to provide guidance
• Inconsistent standards
• Practices not harmonized
• NSO needs to lead in this area / set standards
• One-off data collections create problems
• International estimation difference

14. On their own,
statistics are just
numbers

15. Who are
you
talking
to?

16. Metadata for presentation with data

17. Metadata presented with data
Mandatory metadata 1. Title describing data being presented
2. Data provider
3. Statistical concepts and definitions
Conditional metadata 4. Comparability (geographical / over time)
5. Source data
6. Symbols or abbreviations
Optional metadata 7. Accuracy
8. Contact information
9. References / Relevant links

18. Metadata about an overall data series
1.Name of data series
2.Goal and target addressed
3.Method of computation
4.Definition
5.Rationale
6.Sources and data collection
7.Gender issues
8.Comments and limitations
9.Availability

19. National activities
1. Convince management about need for action
2. Create awareness about importance of metadata
3. Establish a technical working group on metadata
4. Develop metadata framework and strategy
5. Create a metadata-friendly culture
6. Develop standards and produce metadata tools
(e.g. national compendiums, guidelines,
templates)
7. Produce a training manual

20. National activities
8. Train statisticians / other data producers in
writing metadata
9. Collect, edit and compile national MDG-
related metadata from across the NSS
10.Disseminate metadata (hard and soft copy)
11.User-producer workshops to get feedback
12.Create a data quality assessment framework
13.Ensure AU Handbook is used by the NSS

21. Regional activities
1. Campaign for action / convince heads of NSOs
2. Agree on a minimum standard for writing
metadata
3. Translate metadata guide into other languages
4. In-depth training on SDMX (train the trainer)
5. Further training on metadata
6. Collate national metadata at the regional level
7. Create technical committee to review
metadata and provide feedback to NSOs
8. Compile and publish regional metadata

22. Regional activities
9. Needs assessment to identify gaps in statistical
capacity
10.Standard set of indicators, AU handbook and
legislation
11.Build adequate capacity in implementing a
quality framework statistics

23. Expectations of the workshop
• Better understanding / knowledge produce and
disseminate better metadata
• Tools to apply what we learn
• Develop skills of other data producers
• Get managerial support: resources and will
• Guidance on how to customize MDG metadata
to reflect national practices
• How to build on what NSOs have already done

24. Expectations of the workshop
• SDMX: what is it and how to implement?
• Standard format for writing metadata
• How to narrow the gap between different data
sources?
• How to build a data warehouse?
• Resolve international and national discrepancies

25. What are metadata? Provide a short
definition.
Answer: metadata are data that
defines or describes other data.

26. What metadata would you expect to
be included with data presented in a
table?
Answer: a clear title , column / row
labels, footnotes , data provider,
source of the data…

27. Why is metadata particularly
important when reporting on
development indicators, such as the
MDGs?
Answer:
• indicators often have multiple data sources
• users of MDG reports may have limited
experience in interpreting statistics
• differences in MDG estimates

28. What benefits can be gained by
improving the way national
statistical offices produce and
manage metadata?

29. Benefits of managing metadata
• Use up-to-date classifications and definitions
• Gain resources
• Increase morale and productivity
• Capitalising on lessons learned
• Make it available to users
• Easier for data users to understand
• Increased trust in official statistics

30. What are some tips / advice for
writing good metadata?

31. Answers include:
• Be aware of the target audience
• Use clear and simple language
• Keep sentences and paragraphs short
• Avoid technical terms, jargon and acronyms
• Ask colleagues to review the data and metadata
– do they make sense?
• Use a standard glossary of terms for consistency
• Develop publication or style manuals for how
data / metadata are presented