SPACE-TIME RESEARCH

STATISTICAL COMMUNICATION

Swiss Statistics MeetingLuzern, 14-16 November 2007

Space-Time Research - John EllenbergerELCA- Judith Blank

Competing forces – data availability

1980’s 1990’s 2000’s

Privacy protectionRevenue earningError preventionStatistical purity

Less data availableGovt. policyTransparency

ROI for statisticsUser expectations

TechnologyInformation explosion

More data available

Statistical tug-of-war

2010 ?

The information revolution

1980’s 1990’s 2000’s

Privacy protectionRevenue earningError preventionStatistical purity

Less data availableGovt. policyTransparency

ROI for statisticsUser expectations

TechnologyInformation explosion

More data available

2010 ?

Where do people look for information?

The issues with statistical communication

1. Tell a story or present the facts?

2. Feed collaboration sites?

3. Ensure people don’t make mistakes – duty of care

4. Privacy protection

5. Integration with other statistical data

6. Robustness versus timeliness and coverage

7. Question > Answer > Question > Answer…………… discovery, innovation, Creativity

1. Tell a story?

Should statistical agencies provide more value to the data by helping users understand what is going on?

Or should agencies simply present the numbers?

Once you provide any sort of visualisation you are, by default, choosing what data to highlight.

Does it really matter?

1. Tell a story?

1. Tell a story?

1. Tell a story?

2. Feed collaboration sites?

2. Statistical democracy

3. Duty of care

Ensure people don’t misinterpret the data

Sample error

Survey methodology

Full Metadata

Easy to use software

What to count

4. Privacy protection

Ensure no individual or business can be identified

Aggregated data or micro data?

What is considered to be sensitive

Increase computer power and new privacy protection techniques now make it possible for unit record access over the Internet

Australian Bureau of Statistics – Table Builder

US Census Bureau – Advanced Query system

Some of the methods

Random rounding (good for social data)

Cell suppression (3/80 rule)

Tau Argus (Consequential suppression issue)

Business rules (restrict query type)

Mean cell size plus other geographic checks

Perturbation / additivity

4. Privacy protection – random rounding

4. Privacy protection – consequential suppression

5. Integration with other statistical data

The sum of the data is worth more than the individual components

BUT the data must be comparable........

Hea

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Em

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Tax

Ben

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Geography

Subject Population

Time

Classifications, concepts, concordances and meta information

6. Robustness versus timeliness and coverage

COVERAGEThe depth of the data

TIMELINESSHow timely the data is

ROBUSTNESSHow reliable, correct the data is

The need for data now………..

7. Innovation and Creativity....

Overall trend in Statistical Communication is to enable users to ask questions………. Power to the analytical amateurs

Question?

AnswerQuestion?

Answer Question?

Answer

Discovery, innovation….. Creativity

SPACE-TIME RESEARCH

Danke!Merci!Grazie!Thank you…

Global trends for Statistical Agencies

The continuing battle between making data available and protecting official statistics……

In the green cornerEconomies are looking to maximise their return on investment in official statistics

The Internet makes it possible for the marginal cost of disseminating statistics to be zero

General trend to see official statistics as a public good and treat them as a national resource

In the red cornerPrivacy is increasingly becoming as issue

Respondent burden and attitudes towards supplying data are changing

Statistical agency budgets are under pressure

Statistical agency web sites may not be users first port of call for statistics