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Summary of workshop
Workshop on Writing Metadata for Development Indicators
Lusaka, Zambia30 July – 1 August 2012
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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
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Source: International Labour Organization (ILO), Guide to the new Millennium Development Goals Employment Indicators including the full set of Decent Work Indicators, 2009.
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UNDP Guide to Measuring Human Development
“… a reference tool that provides guidance on statistical principles…”
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Types of metadata
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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 outputsSource: Graeme Oakley, Australian Bureau of Statisticswww.unescap.org/stat/apex/2/APEX2_S.4_conference_Statistical%20Metadata%20Standards.pdf
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Existing guidance
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Metadata and development indicators
• indicators often have multiple data sources
• users may have limited knowledge of statistics
• discrepancies in MDG estimates
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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
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Challenges you faceWithin 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
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Challenges you faceOutside 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
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On their own, statistics are just
numbers
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Who are you
talking to?
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Metadata for presentation with data
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Metadata presented with data
Mandatory metadata 1. Title describing data being presented2. Data provider3. Statistical concepts and definitions
Conditional metadata 4. Comparability (geographical / over time)5. Source data6. Symbols or abbreviations
Optional metadata 7. Accuracy8. Contact information9. References / Relevant links
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Metadata about an overall data series
1.Name of data series2.Goal and target addressed3.Method of computation4.Definition5.Rationale6.Sources and data collection7.Gender issues8.Comments and limitations9.Availability
1.Name of data series2.Goal and target addressed3.Method of computation4.Definition5.Rationale6.Sources and data collection7.Gender issues8.Comments and limitations9.Availability
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National activities1. Convince management about need for action2. Create awareness about importance of
metadata3. Establish a technical working group on
metadata4. Develop metadata framework and strategy5. Create a metadata-friendly culture 6. Develop standards and produce metadata
tools (e.g. national compendiums, guidelines, templates)
7. Produce a training manual
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National activities8. Train statisticians / other data producers in
writing metadata9. Collect, edit and compile national MDG-
related metadata from across the NSS10.Disseminate metadata (hard and soft copy)11.User-producer workshops to get feedback12.Create a data quality assessment framework13.Ensure AU Handbook is used by the NSS
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Regional activities1. Campaign for action / convince heads of NSOs2. Agree on a minimum standard for writing
metadata3. Translate metadata guide into other
languages4. In-depth training on SDMX (train the trainer)5. Further training on metadata6. Collate national metadata at the regional
level 7. Create technical committee to review
metadata and provide feedback to NSOs8. Compile and publish regional metadata
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Regional activities9. Needs assessment to identify gaps in
statistical capacity10.Standard set of indicators, AU
handbook and legislation11.Build adequate capacity in
implementing a quality framework statistics
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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
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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
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What are metadata? Provide a short definition.
Answer: metadata are data that defines or describes other data.
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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…
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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
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What benefits can be gained by improving the way national statistical offices produce and manage metadata?
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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
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What are some tips / advice for writing good metadata?
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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