Making
Sense
of the
Semantic
Web
Nova Spivack
CEO & Founder
Radar Networks
Radar Networks

About This Talk
• Making sense of the semantic sector
• How the Semantic Web works
• Future outlook
• Twine.com
• Q&A
Radar Networks

The Big Opportunity…
The social graph just connects people
The semantic graph connects everything
People
Companies Emails And it uses richer
semantics to enable:
Places Products
Better search
Interests Services More targeted ads
Smarter collaboration
Activities Web Pages
Deeper integration
Projects Documents
Richer content
Events Multimedia Better personalization
Groups
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The third decade of the Web
• A period in time, not a technology…
• Enrich the structure of the Web
o Improve the quality of search, collaboration, publishing, advertising
o Enables applications to become more integrated and intelligent
• Transform Web from fileserver to database
o Semantic technologies will play a key role
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The Intelligence is in the Connections
Intelligent Web
Web OS
Web 4.0
2020 - 2030
Intelligent personal agents
Semantic Web
SWRL
Web 3.0 Distributed Search
OWL 2010 - 2020
OpenID AJAX SPARQL Semantic Databases
between Information Social Web RSS
ATOM
Semantic Search
Widgets
P2P RDF Mashups
Office 2.0
Javascript
SOAP XML
Flash Web 2.0
The Web Java 2000 - 2010 Weblogs Social Media Sharing
HTML
HTTP SaaS Social Networking
Directory Portals Wikis
VR
Keyword Search Lightweight Collaboration
The PC BBS Gopher Web 1.0 Websites
1990 - 2000
MMO’s MacOS SQL
Groupware
SGML Databases
Windows
File Servers
The Internet
PC Era
FTP IRC Email 1980 - 1990
USENET
PC’s File Systems
Connections between people
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Beyond the Limits of Keyword Search
The Intelligent Web
Web 4.0
ctivity of Search 2020 - 2030 Reasoning
The Semantic Web
Web 3.0 Semantic Search
2010 - 2020
The Social Web
Natural language search
The World Wide Web
Web2010
2000 -
2.0
Tagging
Web2000
1990 -
1.0
Keyword search
The Desktop
Directories
PC Era
1980 - 1990
Files & Folders
Databases
Amount of data
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Five Approaches to Semantics
• Tagging
• Statistics
• Linguistics
• Semantic Web
• Artificial Intelligence
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The Tagging Approach
• Pros • Technorati
o Easy for users to add and read
tags • Del.icio.us
o Tags are just strings
o No algorithms or ontologies to
• Flickr
deal with
o No technology to learn
• Wikipedia
• Cons
o Easy for users to add and read
tags
o Tags are just strings
o No algorithms or ontologies to
deal with
o No technology to learn
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The Statistical Approach
• Pros: • Google
o Pure mathematical algorithms
o Massively scaleable • Lucene
o Language independent
• Autonomy
• Cons:
o No understanding of the content
o Hard to craft good queries
o Best for finding really popular
things – not good at finding
needles in haystacks
o Not good for structured data
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The Linguistic Approach
• Pros: • Powerset
o True language understanding
o Extract knowledge from text • Hakia
o Best for search for particular
facts or relationships • Inxight, Attensity, and others…
o More precise queries
• Cons:
o Computationally intensive
o Difficult to scale
o Lots of errors
o Language-dependent
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The Semantic Web Approach
• Pros: • Radar Networks
o More precise queries
o Smarter apps with less work • DBpedia Project
o Not as computationally intensive
o Share & link data between apps • Metaweb
o Works for both unstructured and
structured data
• Cons:
o Lack of tools
o Difficult to scale
o Who makes all the metadata?
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The Artificial Intelligence Approach
• Pros: • Cycorp
o This is the holy grail!!!!
o Approximates the expertise and
common sense reasoning ability
of a human domain expert
o Reasoning / inferencing,
discovery, automated assistance,
learning and self-modification,
question answering, etc.
• Cons:
o This is the holy grail!!!!
o Computationally intensive
o Hard to program and design
o Takes a long time and a lot of
work to reach critical mass of
knowledge
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The Approaches Compared
Make the Data Smarter
A.I.
Semantic
Web
Linguistics
Tagging
Statistics
Make the software smarter
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Two Paths to Adding Semantics
• “Bottom-Up” (Classic)
o Add semantic metadata to pages and databases all over the Web
o Every Website becomes semantic
o Everyone has to learn RDF/OWL
• “Top-Down” (Contemporary)
o Automatically generate semantic metadata for vertical domains
o Create services that provide this as an overlay to non-semantic Web
o Nobody has to learn RDF/OWL
-- Alex Iskold
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In Practice: Hybrid Approach Works Best
Tagging
Semantic Web
Top-down
Statistics
Linguistics
Bottom-up
Artificial intelligence
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A Higher Resolution Web
IBM.com
Web Site
Joe
Person Lives in Palo Alto IBM
City Company
Publisher of
Fan of
Subscriber to Lives in
Employee of
Sue
Jane Person
Dave.com Person
RSS Feed Fan of
Coldplay
Band Friend of
Member of
Depiction of
Design Married to
Source of Team Member
Group 123.JPG
of
Dave.com Bob Photo
Weblog Person
Depiction of
Member of
Dave Stanford Member of
Author of Person Alumnae
Group
Member of
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The Web IS the Database!
Application A Application B
IBM.com
Web Site
Joe
Person IBM
Palo Alto
Lives in City Company
Publisher of
Fan of
Subscriber to Lives in
Employee of Sue
Jane Person
Dave.com Person
RSS Feed Coldplay
Fan of
Band
Friend of
Member of
Design Depiction of
Team Married to
Group
Source of Member 123.JPG
of Photo
Dave.com Bob
Weblog Person
Depiction of
Member of
Dave Stanford
Person Alumnae Member of
Author of Group
Member of
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Smart Data
• Smart Data is data that carries whatever is needed to make
use of it:
• Software can become dumber and more generic, yet
ultimately be smarter
• The smarts moves into the data itself rather than being
hard-coded into the software
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The Semantic Web is a Key Enabler
• Moves the “intelligence” out of applications, into the
data
• Data becomes self-describing; Meaning of data becomes part of the data
• Data = Metadata.
• Just-in-time data
• Applications can pull the schema for data only when the data is actually
needed, rather than having to anticipate it
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The Semantic Web = Open database layer for the Web
User Web Ads & Data Apps &
Profiles Content Listings Records Services
Open Query Interfaces
Open Data Mappings
Open Data Records
Open Rules
Open Ontologies
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Semantic Web Open Standards
• RDF – Store data as “triples”
• OWL – Define systems of concepts called “ontologies”
• Sparql – Query data in RDF
• SWRL – Define rules
• GRDDL – Transform data to RDF
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RDF “Triples”
Predicate
Subject Object
• the subject, which is an RDF URI reference or a blank node
• the predicate, which is an RDF URI reference
• the object, which is an RDF URI reference, a literal or a
blank node
Source: http://www.w3.org/TR/rdf-concepts/#section-triples
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Semantic Web Data is Self-Describing Linked Data
Ontologies Definition
Definition
Definition
Definition
Data Record ID
Definition
Field 1 Value
Field 2 Value
Definition Field 3 Value
Field 4 Value
Definition
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RDBMS vs Triplestore
Person Table
S PO Subject Predicate Object
ID f_name l_name 001 isA Person
001 firstName Jim
001 jim wissner 001 lastName Wissner
002 nova spivack 001 hasColleague 002
003 chris jones 002 isA Person
002 firstName Nova
004 lew tucker 002 lastName Spivack
002 hasColleague 003
003 isA Person
003 firstName Chris
Colleagues Table 003 lastName Jones
003 hasColleague 004
SRC-ID TGT-ID 004 isA Person
001 001 004 firstName Lew
001 002 004 lastName Tucker
001 003
001 004
002 001
002 002
002 003
002 004
003 001
003 002
003 003
003 004
004 001
004 002
004 003
004 004
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Merging Databases in RDF is Easy
S PO S P O S PO
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The Growing Linked Data Universe
Twine Yahoo
Freebase
Reuters
OpenCalais
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The Growing Semantic Web
Online Services
Consumers Developers
Applications
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Future Outlook
• 2007 – 2009
o Early-Adoption
o A few killer apps emerge
o Other apps start to integrate
• 2010 – 2020
o Mainstream Adoption
o Semantics widely used in Web content and apps
• 2020 +
o Next big cycle: Reasoning and A.I.
o The Intelligent Web
o The Web learns and thinks collectively
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The Future of the Platform…
• 1980’s -- The Desktop is the platform
• 1990’s -- The Browser / Server is the platform
• 2000’s -- Web Services are the platform
• 2010’s -- The Semantic Web is the platform
• 2020’s -- The WebOS is the platform
• 2030’s -- The Human Body is the platform…?
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A Mainstream Application of
the Semantic Web…
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Twine.com Overview
Organize. Share. Discover.
Around your interests
Using the Semantic Web
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What Can You Do With Twine?
• Organize
o Collect & manage your stuff
• Share
o Author & share content
o Discuss & collaborate
• Discover
o Track Interests
o Search & explore
o Get recommendations
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Differentiation
• Facebook - For your relationships
• LinkedIn - For your career
• Twine - For your interests
Twitter + Del.icio.us + Blogger?
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Twine is Smart
Semantic tagging Semantic linking
Organize
All
Kinds
Of Share
Content
Discover
Recommendations Semantic Search
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Let’s take a look at Twine…
(demo of Twine site…)
Radar Networks

Radar Networks’ Semantic Web Platform
Web App
Twine.com User Portal REST API Bookmarklet RSS Feeds Cache
SPARQL & Email
AJAX, Jetty, PicoContainer, Java, XML, SPARQL Jena, ATOM
KnowledgeBase
Semantic Object Class inferencing Object Query Tuple Cache
& Cache Query
Platform RDF, OWLOntology
TupleStore service
SQL Query Access Control Predicate Remote Cache
Generator Inferencing Access
RDF, OWL, SQL Mina
SQL Database WebDAV File Store
Storage
Relational database Flat File Store
Postgres, webDAV, Isilon
Solaris cluster
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Target Customer
Twine is for active users of the Web, including consumers
and professionals, who create, find and share information
about their interests
Demographics: Interests:
• 18 – 45 years old • Professional associations
• Have many personal interests and hobbies • Alumni groups
• Social connections are important – family, friends, colleagues • Social networks (Facebook, Plaxo, LinkedIn)
• Americans with a household income of $100,000 or more • Volunteer organizations
o Nearly 26 million such consumers used the Internet in • Groups based on interests (hobbies, health, sports,
August 2003, spending an average of 27.6 hours online entertainment, culture, family, technology, user groups, etc.)
-- more than any other income segment. • Participating/working in teams at organizations of all sizes
o Consume an average of nearly 3,000 pages a month,
almost 300 pages more than the average Internet user
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Market Opportunities for Twine
Individuals Groups, Teams and Communities
• Individual consumers • Interest communities
• Support groups
• Individual professionals
• Content publishers
• Users groups
• Hobbyists
• Social groups
• Product communities
• Event communities
• Communities of practice
• Customer support
• Collaborative teams
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Contact Info
• Visit www.twine.com to sign up for the invite beta wait-list
• You can email me at nova@radarnetworks.com
• My blog is at http://www.mindingtheplanet.net
• Thanks!
Radar Networks

Rights
• This presentation is licensed under the Creative Commons Attribution
License.
o Details: This work is licensed under the Creative Commons Attribution 3.0 Unported License. To
view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/ or send a letter to
Creative Commons, 171 Second Street, Suite 300, San Francisco, California, 94105, USA.
• If you reproduce or redistribute in whole or in part, please give
attribution to Nova Spivack, with a link to
http://www.mindingtheplanet.net
Radar Networks