Geoff Lee, August 2006, Rio de Janeiro

on behalf of

Siu-Ming Tam (& Regina Kraayenbrink)UNSD workshop, March 2006, New York

Australian Bureau of Statistics

Emerging Trends and Best Practices in Data Communication

What am I going to cover?�2 areas

ƒ Emerging trends and ABS practices on web publishing–based on Statistics Canada research

ƒ ABS –improving data communication–cognitive psychology theory and practice–examples and prototype

�Questions, time permitting

�Out of scope initiatives but worthwhile mentioning at the start

–adding value to data sets�linked data sets over time, across sources�Granularity eg geocoding

–improving the information content�Google Earth, international comparisons

–improving power of analysis�RADL, GIS

�Happy to expand during discussion, if there is interest

What am I not going to cover?

Emerging international trends

�22 NSOs (mainly from Europe and North America) surveyed by Roy (2005)�NSOs at different stages of migration to web publishing�WWW is the principal means of data dissemination (and other things)�2/3 of NSOs have developed a strategic vision for the WWW

Emerging international trends (cont'd)

�User nominated issuesƒ ease of navigationƒ effective search capability

–Gartner adviceƒ paucity of regional dataƒ easy access to documented methods and

methodologyƒ effective on line retrieval and analysis

Emerging international trends (cont'd)

�NSO nominated issuesƒ content and standardsƒ information management and data presentation toolsƒ meta data presentationƒ more efficient and effective web publishingƒ measurement of web user satisfaction

�NSO expectationsƒ improved navigationƒ thematic based structureƒ improved search capability

Emerging international trends (cont'd)

�80% of NSOs are now providing free on line accessƒ 50% reported rising costsƒ ABS experience

Website pages viewed per month

Free publicationson web

Emerging international trends (cont'd)

�Key issues from Roy's work ƒ Effectively finding, retrieving, analysing and

understanding statistical information published on the web by users, and measuring their satisfaction

�Data dissemination vs data communication

�What? ƒ transmission of statistical information from

statisticians to clients�Why?

ƒ increase users and uses–reason for our existence

ƒ increase informed use of statistics–understand information content, context, caveats and limitations to determine 'fitness for purpose'–decreased likelihood of data misinterpretation/misuse

Improving data communication

�ABS research into cognitive psychology showed three important cognitive processes:ƒ attention - using stimuli to focus the mind on important

information–cognitive overload and filtering–moving things and stimuli

ƒ perception - attaching meaning to sensory information eg symbols, objects, texts–recognising patterns–organisational cues

ƒ learning - encoding information in long term memory.

How does the mind comprehend data?

�Key influencing factors:ƒ Alerting techniques - make statistics/stories

visibleƒ Reduce cognitive load - memory constraintsƒ Presentational cues - Gestalt laws to maximise

pattern recognition and perceived affordanceƒ Clarity/familiarity/complexity of content - simple

to complex presentation (Elaboration Theory; Given-New strategy); reduce propositional complexity; write for the web

ƒ Contextual linking of metadata with data

How to maximise comprehension?

�Key strategies:ƒ Use organisation cues and alerting techniquesƒ Layer information from "simple" to "complex"ƒ Ensure density of information suits audience and

purposeƒ Improve 'Writing for Web'ƒ Provide guidelines for ABS authorsƒ Contextually link metadata from statistical

data/statistical termsƒ Data visualisation initiatives

From theory to practice - ABS approaches

Layering of informatione.g. electronic publication vision

1st Layer

Headlines

2nd Layer

Short Summary

3rd Layer

More detailed material

4th Layer

Detailed data

�Short web pages (in general)�Longer documents (in some situations)

ƒ but Chunking up and linking stories

�Use graphs to summarise data�Avoid large tables in summary documents

Ensure density of information suits audience and purpose

Examples and Prototype

• Alerting techniques• Statbox• RSS

• Organisation cues• chunking up and bundling

• Layering of information• Density and web writing

• example 1• example 2

StatBox

Email and RSS notification

Retail survey description ...

Retail survey description ... 9 screen pages later

Electronic Publication Current Example

Prototype

�Contextual linking of metadata from statistical data

�www.abs.gov.au/about/ePublication

Bundling level 1

Data Visualisation• Population pyramid• Dashboard http://www.math.yorku.ca/SCS/Gallery/• Map examples• 2-D• 3-D• Evolving business cycle

http://www.cbs.nl/en-GB/menu/themas/macro-economie-financiele-instellingen/conjunctuurgegevens/publicaties/conjunctuurbericht/klok/ck-homepage.htm

• Making Statistical Stories Interesting

• GapMinder (just google Gapminder)• MDG http://mdgs.un.org

Comparing regions

Data Visualisation

• Making Statistical Stories Interesting• GapMinder• MDG (the Millenium Development

Goals)

Thanks for listening