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United Nations Economic Commission for Europe Statistical Division UNECE Training Workshop on Dissemination of MDG Indicators and Statistical Information.

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Presentation on theme: "United Nations Economic Commission for Europe Statistical Division UNECE Training Workshop on Dissemination of MDG Indicators and Statistical Information."— Presentation transcript:

1 United Nations Economic Commission for Europe Statistical Division UNECE Training Workshop on Dissemination of MDG Indicators and Statistical Information Astana, Kazakhstan 23 – 25 November 2009 Steven Vale, UNECE Measuring and Communicating Data Quality

2 Steven Vale - UNECE Statistical Division Slide 2  What is quality?  How can we measure quality?  How should we report and communicate quality? Contents

3 Steven Vale - UNECE Statistical Division Slide 3 Which is the Best Quality?

4 Steven Vale - UNECE Statistical Division Slide 4 Definition of Quality International Standard ISO 9000/2005 defines quality as; 'The degree to which a set of inherent characteristics fulfils requirements.’

5 Steven Vale - UNECE Statistical Division Slide 5 What Does This Mean?  Whose requirements? The user of the goods or services  A set of inherent characteristics? Users judge quality against a set of criteria reflecting the different characteristics of the goods or services  So quality is all about providing goods and services that meet the needs of users (customers)

6 Steven Vale - UNECE Statistical Division Slide 6 Quality Criteria

7 Steven Vale - UNECE Statistical Division Slide 7 Quality Criteria for Statistics  Different statistical organisations use different criteria - but lists of criteria are quite similar  UNECE list: RelevanceComparability AccuracyClarity TimelinessAccessibility Punctuality

8 Steven Vale - UNECE Statistical Division Slide 8 Relevance  Are the statistics that are produced needed?  Are the statistics that are needed produced?  Do the concepts, definitions and classifications meet user needs?

9 Steven Vale - UNECE Statistical Division Slide 9 Accuracy  The closeness of statistical estimates to true values  In the past: Quality = Accuracy  Now accuracy is just one part of quality

10 Steven Vale - UNECE Statistical Division Slide 10 Timeliness  The length of time between data being made available and the event or phenomenon they describe Punctuality  The time lag between the actual delivery date and the promised delivery date

11 Steven Vale - UNECE Statistical Division Slide 11 Comparability  The extent to which differences are real, or due to methodological or measurement differences Comparability over time Comparability through space (e.g. between countries / regions) Comparability between statistical domains (sometimes referred to as coherence)

12 Steven Vale - UNECE Statistical Division Slide 12 Accessibility  The ways in which users can obtain or benefit from statistical services (pricing, format, location, language etc.) Clarity  The availability of additional material (e.g. metadata, charts etc.) to allow users to understand outputs better

13 Steven Vale - UNECE Statistical Division Slide 13 Importance of Accessibility  Not just about making data available on the Internet or in a book Passive accessibility  Accessibility is about bringing data to users in an understandable way, opening a dialogue with those users, and ensuring that their information needs are met Active accessibility

14 Steven Vale - UNECE Statistical Division Slide 14 Accessibility Should Include:  Communicating  Marketing  Interpreting  “Story-telling”  Informing  Educating

15 Steven Vale - UNECE Statistical Division Slide 15 Accessibility and Visualization  Good visualizations make data accessible to many more users  Bad visualizations are unhelpful / misleading  “Self-service” visualization needs to be simple, with guidance to help users get meaningful results  “Ready-made” visualizations can be more complex, tailored to specific data sets

16 Steven Vale - UNECE Statistical Division Slide 16  Is it more cost-effective to: develop “ready-made” graphics, or offer users more “self-service” functionality?  Many users don’t have the time or knowledge to produce good visualizations  Advanced users have access to their own visualization and analysis tools Accessibility and Visualization

17 Steven Vale - UNECE Statistical Division Slide 17 Importance of Clarity  Clarity is all about explaining data  Do current explanatory notes help? Often written by specialists for specialists Full of jargon Too long Too boring!  Simplified, plain-text versions needed

18 Steven Vale - UNECE Statistical Division Slide 18 Other Considerations  Cost / efficiency  Integrity / trust  Reputation of the organization  Professionalism Adherence to international standards (e.g. UN Fundamental Principles of Official Statistics)

19 Steven Vale - UNECE Statistical Division Slide 19 Quality is not just about outputs  To have good outputs we need to have good inputs and processes, so we need to think about the quality of these as well InputProcessOutput

20 Steven Vale - UNECE Statistical Division Slide 20 Quality of Inputs  Timeliness  Completeness – are there any missing units or variables?  Comparability with other sources  Quality check survey?  Knowledge of the source is vital!

21 Steven Vale - UNECE Statistical Division Slide 21 Quality of Processing  Quality of matching / linking  Outlier detection and treatment  Quality of data editing  Quality of imputation  Keep raw data / metadata to refer back to if necessary

22 Steven Vale - UNECE Statistical Division Slide 22 Quality of Outputs  Are the users satisfied?  Are the outputs comparable with data from other sources?  What is the impact on time series?  Are the outputs cost-effective?  Quality reports to measure and communicate differences?

23 Steven Vale - UNECE Statistical Division Slide 23 Measuring Quality  Quantitative methods E.g. confidence intervals  User surveys  Self evaluation  Benchmarking

24 Steven Vale - UNECE Statistical Division Slide 24 Quantitative Measures The tops of the bars indicate estimated values and the red lines represent the confidence intervals surrounding them.

25 Steven Vale - UNECE Statistical Division Slide 25 UNECE Database User Survey  Launched each autumn on database web site  10 questions  150 responses (target 100)

26 Steven Vale - UNECE Statistical Division Slide 26  Design a user survey with up to 10 questions for users of your web site  20 minutes Exercise

27 Steven Vale - UNECE Statistical Division Slide Type of user 2. Frequency of use 3. Location (country) 4. Type of data 5. Database relevance 6. Timeliness UNECE User Survey Questions

28 Steven Vale - UNECE Statistical Division Slide 28 Continued Clarity (metadata) 8. Overall data quality 9. User interface 10. Other comments and questions

29 Results: Type of user

30 Results: Frequency of use

31 Results: Location

32 Results: Data quality

33 Results: User interface

34 Steven Vale - UNECE Statistical Division Slide 34 Improving Our Services  Better timeliness of data  New “Country Overview” data cube to give quick access to key indicators  More content in Russian  Improved user interface  More and better metadata  Statistical literacy

35 Steven Vale - UNECE Statistical Division Slide 35  Relatively quick and cheap  Is it sufficiently objective?  Needs a standard framework to ensure comparability of quality assessments Eurostat DESAP check list: /portal/quality/documents/desap%20G0- LEG EN.pdf Self-evaluation

36 Steven Vale - UNECE Statistical Division Slide 36  Comparing data values or data production processes between two sources  Differences can be studied to try to find ways to improve quality Benchmarking

37 Steven Vale - UNECE Statistical Division Slide 37 Benchmarking Between Countries  Fairly cheap and easy way to get ideas on how to improve statistical processes  Mutual benefit - “win - win”  Helps to improve international cooperation  May lead to joint development projects

38 Steven Vale - UNECE Statistical Division Slide 38  Quality Reports Summary – “traffic light” indicator  Red – Serious quality issues, read the quality report before using  Orange – Caution, do not use for important decisions without reading the quality report  Green – Good quality Intermediate – short quality report (1000 words maximum) Detailed – full quality report Communicating Quality

39 Steven Vale - UNECE Statistical Division Slide 39  Should cover all components of quality  Should be written for the user  Should be easily accessible  Should follow a standard template Detailed Quality Reports

40 Steven Vale - UNECE Statistical Division Slide 40 Exercise  What should be covered in a detailed quality report? List the topics that should be included  10 minutes

41 Steven Vale - UNECE Statistical Division Slide 41  Introduction to the statistical process and its outputs  Relevance  Accuracy  Timeliness  Punctuality  Accessibility  Clarity ESQR Contents (1)

42 Steven Vale - UNECE Statistical Division Slide 42  Comparability  Trade-offs between quality components  Assessment of User Needs and Perceptions  Performance, Cost and Respondent Burden  Confidentiality, Transparency and Security  Conclusion ESQR Contents (2)

43 Steven Vale - UNECE Statistical Division Slide 43  Quality is all about meeting user needs  There are many different aspects to quality, some of which may be in conflict E.g. Timeliness versus Accuracy  There are various ways of measuring quality; user views are important  Quality should be communicated to users in a way they can understand Summary

44 Steven Vale - UNECE Statistical Division Slide 44 Which is the Best Quality? It depends what the user needs!

45 Steven Vale - UNECE Statistical Division Slide 45 Questions?


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