Data management
and
communication
issues
by Siu-Ming Tam
Information Management and
Census Division
5-6 September, 2006,
Melbourne
What am I going to cover?
Data communication
why, whats and hows
upstream processes
data dissemination and data management
ABS strategies and actions to achieve data communication
may/may not apply to the communication of indicators
2006 Census output plans - time permitting
A statistical processing model
Design
Evaluate
Communicate
Disseminate
Collect
Process
Manage
A statistical processing model (cont'd)
"Design" to address statistical needs and objectives
what is a good indicator? Which indicator?
what is a community?
drill down/roll up capabilities?
"Manage" to ensure consistency and coherence of meta
data and statistical data
policy/protocol for data access, change and archival
particularly important for regular releases
reputation management - one single version of "truth"
efficiency - writing once/publishing many times
Output warehouse model
Dissemination vs Communication
Output vs outcomes
Key factors for communication
Content itself
Story telling
Presentation of the materials
Data Communication
What?
sharing of information between producers of statistics to
users in a way that enables understanding
2-way communication
Why?
increase informed use of indicators
understand information content, context, caveats and
limitations to determine 'fitness for purpose'
decreased likelihood of data misinterpretation/misuse
How? - how does the mind comprehend information?
How does the mind comprehend
information?
Cognitive psychology and cognitive processes:
perception - attaching meaning to sensory information
attention - focusing on sensory information
learning - reinforcing or coding into long term memory
presentational methods not a distraction for learning
new information from statistics
How to maximise comprehension?
Presentational issues
appropriate cognitive load
appropriate organisation cues - "context shrinks"
use alerting techniques - attention "economics"
Content issues
simple to complex presentation
reduce propositional complexity
write for the audience
contextually link metadata and statistical data
How to maximise comprehension?
(cont'd)
Tell interesting statistical stories
Allow users to discover patterns in statistical data
From theory to practice - ABS key
strategies
Presentational
Use Gestalt Laws and alerting techniques
Organise information in layers - tourists/harvestors/miners
hence broadcasting
Ensure density of information suits audience and purpose
Content
Link metadata and statistical data contextually
Improve 'Writing for Web' - web surfers behaviours
From theory to practice - ABS key
strategies (cont'd)
Data visualisation
Develop interesting stories
Help people detect patterns in the data
Examples and prototypes
 Contextual linking of metadata from statistical data - a
prototype
 www.abs.gov.au/about/ePublication
 Making statistical stories interesting - data visualisation
 Population pyramid
 Dashboard
 GapMinder
 MDG
Issues
What tools to use to tell interesting stories about indicators?
How to manage the community indicators and metadata?
What policy and standards need to be put in place?
How to create the relevant culture for supporting data
management?
How to communicate metadata to assist interpretation of
indicators?
One warehouse, or eight warehouses?
What role can NDN play in all these?
2006 Census outputs
Paper products
Statistician's report
Social Atlases
Static web based products
Quick statistics
Quick maps - Social Atlases on line
Census tables
Community profiles
2006 Census outputs (cont'd)
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Dynamic web based products
Census on-line
"slicing and dicing of data cubes" + mapping capabilities
Table Builder
generating census tables via 100% file with built in
confidentiality protection
Release schedule
Progressively released from Jul/Aug 07
Pricing - all free except Table Builder
Demonstration - time permitting