Donn DeBoard

1. Donn R. DeBoard
STC‐PMC Annual Conference
March 27, 2010

2. About the presenter
24 years in software documentation
Senior Information Developer,
Vertex Inc. in Berwyn, PA
Senior STC‐PMC member
Judge in local and international communication
competitions
Information Architecture Institute
Usability Professionals Association
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3. What about you
Share a little about
yourself
Share your reasons for
coming to this
conference
Any first time attendees
here
Share your expectations
for this session
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4. Agenda
Information overload and Attention Economy
Confluence of technology trends:
The Web
Social media
User‐generated content
An evolving reader
Personalization: social architecture for information
An evolving communicator
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5. Why is this important
Evolving content over
multiple distribution
methods
Product and service
documentation goes to a
more technically savvy
audience
Communicators need to
be actively engaged in
creating discoverable
content in future
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6. Documentation in the clouds
Our world of in‐house
authoring of proprietary
help files, closed doc
sets, and isolated
knowledge bases is
coming to an end
M.Hiatt
Applications
Data
Personalized
content
Applications
Data
Personalized
content
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7. Information overload
and the Attention Economy
Information overload Attention Economy
Web enables everyone to
create, distribute, and
consume content globally
Content creation outpaces
our ability to consume
content
Attention Economy: endless
status updates and new
content for 24/7 viewing
READ ME FIRST
Source: P. Cashmore
Content creators are battling
for user attention
Source: K.Kelly
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8. Evolution of the web
2009 web trends
2010 web trends
Web 1.0 to Web 3.0
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9. 2009 evolution of the web
• Structured data
• Real time web
• Personalization
• Mobile web and
augmented reality
• Internet of things
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10. Evolution highlights
Structured data:
semantically marked‐up
data enhances content
discoverability on web
Real‐time web:
public and real time
exchange of information
(Twitter, Facebook)
Personalization:
personal or social
attributes reflected in
focused content
Mobile web and
augmented reality (AR):
AR is world view enhanced
by computer‐generated
images
Internet of things:
Internet‐enabled objects
with web services, such as
IBM’s Pachube (PATCH‐
bay)
Source: R.MacManus
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11. 2010 destination of the web
Content curation:
friends become filters for
your content, such as web
bookmarks
Decision Engines:
Hunch: questions and
collective knowledge
Aardvark: in‐network
response
Fame: social media makes
everyone known and
recognized
Source: P. Cashmore
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12. Web 1.0 (1989‐1999)
Desktop search paradigm
Web viewed as a collection
of documents
Relevancy determined by
how closely search criteria
were met
Search results returned
hierarchically based on key
criteria
Source: N. Spivak
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13. Web 2.0 (1999‐2009)
Web of trust around
people and relationships
Introduces social search
Social value in
recommendations, rating,
sharing, linking
Organizes information
around people and
relationships
Social value shows how
community valued
information (rated content)
Source: N. Spivak
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14. Web 3.0 (2009‐2019)
Shift in search paradigm
Current social search engines
(Digg and Twine) rank
content by activity and social
value.
New paths for search
relevancy
Timeliness
Personalization
Past to present
Social to personalization
Source: N. Spivak
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15. New search features
Search engine adaptations to
get personal results
Better ways to understand
content
Metadata is used to
determine what content is
Modified algorithms to
personalize search (Hunch,
Aardvark)
Tailor search to knowledge of
searcher (novice or expert)
Source: N. Spivak
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16. Social identity of web site visitor
Community:
affiliations with others
with similar interests
Location:
mobile location and time
Social:
influence from trusted
peers
Behavior:
individual actions on web
Preferences:
articulated interests
Source: J. Tsai
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17. Web sites evolve into web services
Unstructured information
changed into structured
information
Web services semantically
mark up unstructured
HTML into meaningful
categories
OpenCalais
Google Rich Snippets
Wolfram Alpha
Source: R. MacManus
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18. Evolution of social media
Social relationships
(Start: 1995
Maturity: 2003‐2007)
Social functionality
(Start: 2007
Maturity: 2010‐2012)
Social colonization
(Start: 2010
Maturity: 2012)
Social commerce
(Start: 2011
Maturity: 2013)
Source: J. Tsai
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19. Highlights of social media
Social relationships:
individuals connect with
online groups with simple
profile and discussion
features
Social functionality:
social network as
operating system.
Embedded web
applications
Social colonization:
most web sites are social.
Peer opinions influence
product choice
Social context:
personalized content to
site visitors who share
social identity
Social commerce:
online groups replace
brands
Source: J. Tsai
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20. Evolution of user‐generated
content with social media
Key Shifts
Finding information is not
a destination, but a
process
Broadcast (centralized)
moves to a networked flow
Internet a forum for all to
distribute content
Individuals as content
mediators
Source: D.Boyd
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21. New challenges: democratization
Access to content is available
to all
Attention is not divided
equally
Content with most attention
is not always most
informative
Example: people pay
attention to content in their
native language
Chinese content will soon get
more attention than English
Source: D.Boyd
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22. New challenges: stimulation
People move to content
that stimulates their
mind and senses
Some content causes an
emotional response. But,
this may not be best
content
Over stimulation with
too much information
Source: D.Boyd
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23. New challenges: homogeneity
In a networked world,
people connect to
people like themselves
Similar interests
encourage exchange of
information
Information flow can
create social divides
Differing points of view
need to be heard
Source: D.Boyd
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24. New challenges: power
The ability to get other
people’s attention
Influence their
decisions
Exchange information
New type of
information broker is
emerging
Source: D.Boyd
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25. An evolving reader
We don’t read with
concentration and focused
attention (not linearly)
We are the Google
Generation ‐ scan and
browse multiple sites
quickly
We are decoders of
information
Dilemma: How to create
content to be understood
Source: D.Pires
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26. “The medium is the member”
Social media is
experiences based on
relationships with peers
In a real‐time
environment, content
becomes identity
Traditional contextual
analysis shifts to focus
on dynamic social
interactions
Source: S.Goldstein
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27. Metadata: the game changer
Metadata changes the
future of information
Information has unique
tag
Tag defines attributes of
information
New Common Tag
Standard and Zemanta
Personalization of
information is possible
through tagging
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28. Common Tag Standard
New standard that uses RDFa
Resource Description
Framework (RDFa) is a
standard for structured data
in HTML
Includes human and
machine readable tag
Content becomes more
discoverable and connected
Source: J.O’Dell
Source: www.commontag.com
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29. Example
Tagging this session
Each tag applies to one
concept
One tag, optionally, for
human label for concept
Tags can be across a
document or multiple tags
within sections of document
Example tags are customized
for today’s presentation
<body xmlns:ctag=
http://commontag.org/ns#”rel=“ctag:ta
gged>
<span typeof=“ctag:Tag”
resource=“http://rdf.freebase.
com/ns/en.location=Willow
Grove,PA/>
resource=“http://rdf.freebase.
com/ns/en.identity=Donn
DeBoard/>
resource=“http://rdf.freebase.
com/ns/en.content
subject=personalization/>
</body>
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30. What is personalization?
Personalization Recommendation engines
Individuals organizing content
in ways that are relevant,
appropriate, and unique.
Amazon
Recommendation based on:
Personalized: individual past
behavior
Social: past behavior of similar
users
Item: attributes of item itself
Source: R. McManus
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31. Information architecture
and personalization
User profile and
content profile
A business web site with your
preferences
Business context drive
interaction (Amazon/
Pandora)
Content profile: attributes
of content (Music Genome
project)
User profile: attributes of
user (Location,
demographics )
Source: S. Lemieux/K.Instone
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32. Personalization on web
Data portability on web
OpenID: single‐sign on with
same digital identity
Open Social: shares user data
(profiles, friends, activities)
between sites
Attention Profiling Markup
Language (APML)
Unique data about you ‐
likes, dislikes, and interests
Attention profile is shareable
Source: R. McManus
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33. Shift on content delivery
Broadcast from a single
source
Shift from broadcast media
(single source, such as TV
and news media)
Distributor is sole controller
of content
Attention is undivided
Corporate publications are
pushed out
Source: D.Boyd
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34. Shift to personal content
Personal content
Networked and linked
content
Shift to networked and
linked distribution (multiple
sources and social media)
Everyone shares their story
Receiver is organizer of
personal content
Attention is no longer
assumed, but at a premium
Trust becomes key (We
become trusted advisors)
Source: D.Boyd
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35. Social architecture for information
Personal building blocks
Location
Identity
Content subject
Content type
Performance type
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36. Location
Geography is now part of
content
Twitter now has location
component, geocaching
GPS for your content
Location‐based social
networking services
Foursquare
Gowalla
Many others
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37. Identity
Personal details
Demographics
Interests
Roles (job or volunteer
effort)
Preferences
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38. Content subject
Subject of content
Sub‐topics
Content relationships within
topic
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39. Content type
Search by content type
Robert Horn’s Information
Types
Concept
Fact
Structure
Principle
Procedure
Process
Source: R. Horn,
Information Mapping
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40. Performance type
Search by performance
type
Gery’s faces of a complex task
Why do this
What is it
What is it related to
How do I do it
How or why did this happen
Show me an example
Teach me
How does it work
Why does it work like that
Compare this for me
Where am I
What’s next
Source: G.Gery
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41. Doc mashup
Consolidated information
sources from web
Public content integrated
with internal corporate
(documentation sets, wikis,
help, training) and personal
content
Semantically–relevant
knowledge for selected
audience
Communicators as
information manager and
producer
IBM Mashup Center Wiki
Source: M.Hiatt
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42. Future of the Internet
Now in the Middle Ages
in computing
We are moving towards
a blended reality –
information streaming
at us through physical
and digital artifacts
Personal Internet layer –
personal cloud/content
Source: J.Canton
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43. New perspectives
If technology were not
limited…
Icentered web:
Individual as center of
digital universe
Shift from site‐centered to
individual oriented
Contextivity:
personalization becomes
context of i‐centered
interaction
Source: A.Rahav
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44. An evolving communicator
Information Arbitrage
Thomas L. Friedman,
international business writer,
coined term information
arbitrage
Look at world through
multidimensional, multilens
perspective
Convey complexity to others
through simple stories
Source: H. McLeallan
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45. An evolving communicator
Make content
discoverable
Discoverable content
gets attention
Attention leads shared
interactions within
communities
Feedback to
communicator refines
content discoverability
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46. Finding your place in the future
Connect people to
content in Attention
Economy through
tagging data, not actual
text
Attention mediator
Personal content
streams
Information Arbitrage
skills to see big picture.
Build relationships (Ed
Wallace)
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47. Summary
Information overload and Attention Economy
Confluence of technology trends for:
The web
Social media
User‐generated content
An evolving reader
Personalization: social architecture for information
An evolving communicator
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48. Thanks for your participation!
Questions?
Comments?
Other?
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49. My contact information
You are welcome to
contact me with questions
and comments
Email:
donn.deboard@vertexinc.
com
LinkedIn:
http://www.linkedin.com/
in/donndeboard
Twitter: @donndeboard
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50. For more information
Boyd, Danah. “Streams of Content, Limited Attention:
The Flow of Information through Social Media,”
Web2.0 Expo, New York, New York, November 17,
2009, www.danahboyd. org /papers/talks Web2
Expo.html.
Cashmore, Pete. “10 Web trends to watch in 2010,”
December 9, 2009, www.cnn.com/2009/ TECH/12/
03/cashmore.web.trends.2010/index.html.
Common Tag, www.comontag.org.
3/27/2010 Copyright Donn DeBoard 2010 50

51. For more information
Goldstein, Seth. “The Medium is not longer the
message…You Are.” The Washington Post,
www.washingtonpost.com, December 12, 2009.
Gery, Gloria. Electronic Performance Support Systems,
September, 1991. Gery Performance Press.
ISBN‐13: 9780961796815.
Google, Aardvark. www.vark.com .
Hunch. www.hunch.com
Hiatt, Michael. “Documentation in the Cloud (Podcast),”
March 1, 2010. www.mashstream.com.
Hiatt, Michael. “The Doc Mashup” March, 2010.
www.mashstream.com.
3/27/2010 Copyright Donn DeBoard 2010 51

52. For more information
IBM Mashup Center Wiki
http://www‐10.lotus.com/ldd/mashupswiki.nsf.
Instone, Keith. Information Architecture and
Personalization, Argus Center for Information
Architecture @2000, www.agrus‐acia.com.
Krynsky, Mark. “Basics of Attention Profiling through
APML.” October 2007. www.cleverlogs.org /2007/10
/basics‐of‐atten.html.
Lemieux, Stephanie and Doane, Mike. Taxonomy for
Personalization, Earley and Associates, www.Early &
associates.com, January 6, 2010.
3/27/2010 Copyright Donn DeBoard 2010 52

53. For more information
MacManus, Richard. “Top 5 Web Trends of 2009:
“The Real‐Time Web,” www.readwriteweb.com,
September 8, 2009.
MacManus, Richard. “Top 5 Web Trends of 2009:
“Personalization,” www.readwriteweb.com,
September 9, 2009.
MacManus, Richard. “Top 5 Web Trends of 2009:
Mobile Web and Augmented Reality,”
www.readwriteweb.com, September 10, 2009.
3/27/2010 Copyright Donn DeBoard 2010 53

54. For more information
MacManus, Richard. “Top 5 Web Trends of 2009:
Internet of Things,” www.readwriteweb.com,
September 11, 2009.
MacManus, Richard. “Top 5 Web Trends of 2009:
Structured Data,” www.readwriteweb.com, December
26, 2009
O’Dell, Jolie. “Common Tag Brings Standards to
Metadata” www.readwriteweb.com, June 10, 2009.
3/27/2010 Copyright Donn DeBoard 2010 54

55. For more information
Pieres, Denise. “Why don’t we actually read
anymore?” Dancing Uphill, www.dancinguphill.com,
November 11, 2009.
Quitter, Josh. “The future of reading,”
www.CNNMoney.com, February 11, 2010.
Rahav, Ayala. “Contextonomics: The currency of the
attention economy.” www.icentered. Com.
Rahav, Ayala. “Icentered.” www. icentered.com.
3/27/2010 Copyright Donn DeBoard 2010 55

56. For more information
Spivak, Nova. “The Next Generation of Search –
Search 3.0.”, www.twine.com, August 25, 2009.
Terdiman, Daniel. “The future of the Internet on
display at Singularity University.”, CNET News.
March 4, 2010. www.news.cnet.com.
Tsai, Jessica. “Social Media: The Five Year Forecast
(Jeremiah Owyang interview), CRM Magazine,
www.destinationcrm.com, April 27, 2009.
Wallace, Ed. Building Relationships that last, 2009.
www. relationshipcapitalgroup. Com.
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