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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 27 1. 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... 7. 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: http://epp.eurostat.ec.europa.eu/portal/page /portal/quality/documents/desap%20G0- LEG-20031010-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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