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Not so long ago, back in the days of brochure ware online, we used to be glad just to see live data dished up in web sites. It was real, it was (sometimes) up to date, even if it was also inevitably dry, dense and tabular, and was often only there to be looked at. Those of us making web sites then didn’t have too many data presentation options; our challenge was usually just to make it as clean and fast loading as possible. How we have moved on! These days, the web browser is a window onto a sea of rich data. Now, we expect to be able to understand it, personalise how we view it, add our own input to it and transact with it. At the same time, the volume of what is available threatens to overwhelm us. In short, the User Experience of data has changed completely. Public and private sector organisations are increasingly willing and able to expose aspects of their data both internally and externally, and are using the web as a key channel to do so. Looking internationally we are starting to see pressure on governments to ‘open source’ key data holdings to allow organisations, community groups and individuals to re-use it creatively and in ways that government owners would never imagine. The reality is that User Experience designers and Information Architects are more and more likely to be dealing regularly with the challenges of rich data presentation. This talk examines some approaches to the analysis and presentation of rich data sets on the web. Drawing on the presenter’s own direct experiences from large scale projects in the pharmaceutical, educational, aged care and consumer advocacy sectors.
Citation preview
1
SM
S M
anag
emen
t & T
echnolo
gy
or.. Making light work of data
Stephen Hall National Lead, Web Strategy & Information Architecture
28 August 2009
Improving the UX of data rich interfaces
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Definitions
Data Rich
Discrete, objective facts about a thing
or event
Heavy
Full of possibility
Interface…the means by which users interact with a
system
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Qualification & a story
UX Australia peer reviews – earnest pleas:“Focus on real world stuff, please”
But first – let’s talk about Knowledge Management
“This subject is too big”
What this presentation is:• About SMS’s experience over numerous projects….• …involving presentation of sets of data to existing or new audiences….• ….that sought to bring out the potential of the data to satisfy both user and client needs
And what this presentation is not:• We don’t pretend to be expert in all aspects of the UX of data presentation• These were real world projects, with constraints- not necessarily bleeding edge• What I can show in 45 minutes is necessarily limited
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The classic hierarchy
Discrete, objective facts about a thing or event
Data with relevance & purpose
Information with experience, values, insights & context
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The knowledge value chain
Value add Value add
Comprehensible Actionable
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The knowledge value chain
Comprehensible Actionable
The 5 Cs:
•Condensation•Contextualisation•Calculation•Correction•Categorisation
The 5 Cs:
•Condensation•Contextualisation•Calculation•Correction•Categorisation
The 4 Cs:
•Conversation•Connection•Consequences•Comparison
The 4 Cs:
•Conversation•Connection•Consequences•Comparison
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Condensation
Comprehensible
Intr
oduc
tory
, hig
h
leve
l
Exp
lana
tory
, som
e
deta
il
Spe
cific
, det
aile
d
Pre
cise
, tec
hnic
al
Feeds into
Feeds into
Feeds into
Information richness
Eg: Flyer, brochure, top level web page
Eg: Booklet, 2nd level web page
Eg: Book, lower level web page
Eg: Manual, lowest level web page
Feeds into
Feeds into
Feeds into
Low
High
Intr
oduc
tory
, hig
h
leve
l
Exp
lana
tory
, som
e
deta
il
Spe
cific
, det
aile
d
Pre
cise
, tec
hnic
al
Feeds into
Feeds into
Feeds into
Information richness
Eg: Flyer, brochure, top level web page
Eg: Booklet, 2nd level web page
Eg: Book, lower level web page
Eg: Manual, lowest level web page
Feeds into
Feeds into
Feeds into
Low
High
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Contextualisation
Comprehensible
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Calculation
Comprehensible
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Correction
Comprehensible
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Categorisation
Comprehensible
Exposed structureExposed structure
Exposed structureExposed structure
Exposed structureExposed structure
Self streamingSelf streaming
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Conversation
Actionable
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Connection
Actionable
Linking data setsLinking data sets
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Consequences
Actionable
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Comparison
Actionable
Exposing relative valuesExposing relative values
User control over criteriaUser control over criteria
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The overall UX design goal
To reveal or enable Meaning
Inherent in the data- structure, themes
Inherent in the data- structure, themes
Emerging through meta-information
Emerging through meta-information Emerging over timeEmerging over time
Emerging through juxtaposition
Emerging through juxtaposition
Not imposed!
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Of course meaning depends..
…on where you’re coming from
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Behaviours & circumstances
Information seeking behaviour
Known itemKnown itemExploratoryExploratory
Don’t know..Don’t know..Re-findingRe-finding
Circumstances
Novice
Exp
ert
Nov
ice
Expert
SIT
E
SUBJECT MATTER
Multiple, parallel ways for meaning to be revealed
Search, browse, fuzzy search, contextual discovery, non-preferred terms, personalisation, notifications, preference setting, export, best bets, top item showcase……
Fuzzy search, contextual help, tool tips, personalisation, preference setting, notifications, non-preferred terms, cookies, best bets
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Real world examples- overview
593pages
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Real world examples- overview
GroceryChoice
training.gov.au
New site coming
New site coming
Some themes:
•Structure
•Content
•Tools
•Juxtaposition
•Connection
•Visualisation
..for bringing out meaning
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Structure
Find a subset quicklyFind a subset quickly
Expose structureExpose structure
Create your own structure
Create your own structure
Discover unsought infoDiscover unsought info
Find a subset quicklyFind a subset quickly
Expose structureExpose structure
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Content access
Clarity of purposeClarity of purpose
Self streaming
Self streaming
Self eliminationSelf eliminationAnticipated needsAnticipated needs
Non-preferred termsNon-preferred termsContextual supportContextual support
Information scentsInformation scents
ForgivenessForgiveness
“Aquatic invertebrates”
“Edible fats”
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Tools
Decision supportDecision support
Be notifiedBe notified
Save stuffSave stuff
Personalise the viewPersonalise the view
Take stuff awayTake stuff away
ContributeContribute
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Juxtaposition & connection
Side by side version comparisonSide by side version comparison
Juxtaposition of different data setsJuxtaposition of different data sets
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Visual Design
Visual wayfinding systemVisual wayfinding system
Visual wayfinding systemVisual wayfinding system
Jon Hicks- Icons for interaction
Beware of unintended consequences!Beware of unintended consequences!
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Visualisation
http
://w
ww
.info
rmat
ioni
sbea
utifu
l.net
/
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The government data wave
The cathedral vs the bazaarThe cathedral vs the bazaar
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The govt data wave..
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When doesn’t this work?
VolumeVolume ComplexityComplexitye.g. Open Source Intelligence
Autonomy IDOL- revealing structure in unstructured data
Disambiguation of concepts
Faceted results Dynamic multi-dimensional presentation
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When doesn’t this work?
VolumeVolume ComplexityComplexitye.g. Open Source Intelligence
Autonomy IDOL- revealing structure in unstructured data
‘Heat’ in data clustersVideo text analysis
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When doesn’t this work?
VolumeVolume ComplexityComplexitye.g. Open Source Intelligence
Palantir- revealing structure in unstructured data
Entity extraction from multiple data streams
Connecting entities to find the bad guys
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Digressions - tools
One pair of licences to give away. Is it under your seat?
Thanks, guysThanks, guys
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Takeaways
Comprehensible Actionable
To reveal or enable Meaning
The 5 Cs:
•Condensation•Contextualisation•Calculation•Correction•Categorisation
The 5 Cs:
•Condensation•Contextualisation•Calculation•Correction•Categorisation
The 4 Cs:
•Conversation•Connection•Consequences•Comparison
The 4 Cs:
•Conversation•Connection•Consequences•Comparison
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Questions?
