Presentation given at OECD conference, Seoul 2012.

1. StatMine, – prototype
StatMine
an exploration of dissemination data
Edwin de Jonge
Statistics Netherlands
25 September 2012, Seoul

2. an exploration of dissemination data: StatMine
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3. an exploration of dissemination data: StatMine
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4. StatMine, from numbers to analysis
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5. Why StatMine?
• Statistics Netherlands (SN) mission produce
relevant information for:
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Policy makers
Journalists
Citizens
Enterprises
Economists
Social scientists
Etc.
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6. Numbers ≠ Information
StatLine is SN’s online DB (over 1 billion figures)
We know from a user study that:
1. Many interesting patterns in StatLine are not
spotted by users
2. Many important topics in StatLine are scattered
across multiple tables
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7. Example of problem 2
• Policymaker interested in patients with diabetes:
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Visits to medical doctor
Hospital admissions
Mortality
Medication consumption (insuline)
Obesity
Are all different statistical products (from different
sources)!
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8. Data analysis = Data insight
Goal research project StatMine is to provide data
insight by:
• (I) Using data visualisation
• (II) Combining data table fragments
• (III) Deriving variables
All hypotheses (will be) tested with a prototype with
internal and external users.
(I), tested and succesful
(II, III,… ) is work in progress
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9. Chart types
Bar chart
Line chart
Mosaic chart
Bubble/scatter chart
Comparison
Development
Structure
Correlation
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10. Chart type – bar chart
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11. Chart type – line chart
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12. Chart type – mosaic chart
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13. Chart type – bubble chart
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14. Small multiples
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Split chart into different subpopulations
Goal: compare subpopulations
Very little tools offer this functionality!
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15. Small multiples
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16. Composing a chart
Example:
• Year x Region x Gender x Age
• Count
• Mean income
• Employment
categorical variables /
dimensions
Numeric variables / topics
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17. Prototype
• Built in php, javascript (d3)
• Imported 10 StatLine example tables
• Complex tables, e.g.
• Labor participation x gender x cohorts
• Labor market flow per quarter (employed/unemployed)
• Enterprise birth, death and growth x economic activity x
quarter
• Tested on:
• Internal users
• Owners of data
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18. Demo
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19. Evaluation
• Part I : very succesful
• Owners of data want prototype to check their own
data
• Provides insights
• Easy detection of anomalies
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20. Work in progress
• II, Combination of different fragments
• Testing with policymakers (end this year)
• Or “How to glue statistical tables?”
• III, Derive variables + analysis
• Absolute vs relative (per population unit)
• Turnover / # employees
• Etc
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21. Questions?
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