Spivack Blogtalk 2008

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

About This Talk
Making sense of the semantic sector
Making the Semantic Web more useable
Future outlook
Twine.com
Q & A

The Big Opportunity… And it uses richer semantics to enable: Better search More targeted ads Smarter collaboration Deeper integration Richer content Better personalization The social graph just connects people People Groups The semantic graph connects everything Emails Companies Products Services Web Pages Multimedia Documents Events Projects Activities Interests Places

The third decade of the Web
A period in time, not a technology…
Enrich the structure of the Web
Improve the quality of search, collaboration, publishing, advertising
Enables applications to become more integrated and intelligent
Transform Web from fileserver to database
Semantic technologies will play a key role

A Higher Resolution Web Coldplay Band Palo Alto City Jane Person IBM Company Dave Person Bob Person Design Team Group Stanford Alumnae Group IBM.com Web Site 123.JPG Photo Dave.com Weblog Sue Person Joe Person Dave.com RSS Feed Lives in Publisher of Friend of Depiction of Depiction of Member of Married to Member of Member of Member of Fan of Lives in Subscriber to Source of Author of Member of Employee of Fan of

The Web IS the Database! Application A Application B Coldplay Band Palo Alto City Jane Person IBM Company Dave Person Bob Person Design Team Group Stanford Alumnae Group IBM.com Web Site 123.JPG Photo Dave.com Weblog Sue Person Joe Person Dave.com RSS Feed Lives in Publisher of Friend of Depiction of Depiction of Member of Married to Member of Member of Member of Fan of Lives in Subscriber to Source of Author of Member of Employee of Fan of

The Intelligence is in the Connections Connections between people Connections between Information Email Social Networking Groupware Javascript Weblogs Databases File Systems HTTP Keyword Search USENET Wikis Websites Directory Portals 2010 - 2020 Web 1.0 2000 - 2010 1990 - 2000 PC Era 1980 - 1990 RSS Widgets PC’s 2020 - 2030 Office 2.0 XML RDF SPARQL AJAX FTP IRC SOAP Mashups File Servers Social Media Sharing Lightweight Collaboration ATOM Web 3.0 Web 4.0 Semantic Search Semantic Databases Distributed Search Intelligent personal agents Java SaaS Web 2.0 Flash OWL HTML SGML SQL Gopher P2P The Web The PC Windows MacOS SWRL OpenID BBS MMO’s VR Semantic Web Intelligent Web The Internet Social Web Web OS

Beyond the Limits of Keyword Search Amount of data Productivity of Search Databases 2010 - 2020 Web 1.0 2000 - 2010 1990 - 2000 PC Era 1980 - 1990 2020 - 2030 Web 3.0 Web 4.0 Web 2.0 The World Wide Web The Desktop Keyword search Natural language search Reasoning Tagging Semantic Search The Semantic Web The Intelligent Web Directories The Social Web Files & Folders

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…?

Five Approaches to Semantics
Tagging
Statistics
Linguistics
Semantic Web
Artificial Intelligence

The Tagging Approach
Pros
Easy for users to add and read tags
Tags are just strings
No algorithms or ontologies to deal with
No technology to learn
Cons
Easy for users to add and read tags
Tags are just strings
No algorithms or ontologies to deal with
No technology to learn
Technorati
Del.icio.us
Flickr
Wikipedia

The Statistical Approach
Pros:
Pure mathematical algorithms
Massively scaleable
Language independent
Cons:
No understanding of the content
Hard to craft good queries
Best for finding really popular things – not good at finding needles in haystacks
Not good for structured data
Google
Lucene
Autonomy

The Linguistic Approach
Pros:
True language understanding
Extract knowledge from text
Best for search for particular facts or relationships
More precise queries
Cons:
Computationally intensive
Difficult to scale
Lots of errors
Language-dependent
Powerset
Hakia
Inxight, Attensity, and others…

The Semantic Web Approach
Pros:
More precise queries
Smarter apps with less work
Not as computationally intensive
Share & link data between apps
Works for both unstructured and structured data
Cons:
Lack of tools
Difficult to scale
Who makes all the metadata?
Radar Networks
DBpedia Project
Metaweb

The Artificial Intelligence Approach
Pros:
This is the holy grail!!!!
Approximates the expertise and common sense reasoning ability of a human domain expert
Reasoning / inferencing, discovery, automated assistance, learning and self-modification, question answering, etc.
Cons:
This is the holy grail!!!!
Computationally intensive
Hard to program and design
Takes a long time and a lot of work to reach critical mass of knowledge
Cycorp

The Approaches Compared Make the software smarter Make the Data Smarter Statistics Linguistics Semantic Web A.I. Tagging

Two Paths to Adding Semantics
“ Bottom-Up” (Classic)
Add semantic metadata to pages and databases all over the Web
Every Website becomes semantic
Everyone has to learn RDF/OWL
“ Top-Down” (Contemporary)
Automatically generate semantic metadata for vertical domains
Create services that provide this as an overlay to non-semantic Web
Nobody has to learn RDF/OWL
-- Alex Iskold

In Practice: Hybrid Approach Works Best
Tagging
Semantic Web
Top-down
Statistics
Linguistics
Bottom-up
Artificial intelligence

Smart Data
Smart Data is data that carries whatever is needed to make use of it:
Definition of intended meaning and schema
Policies and permissions
Context (links, etc.)
History and schedule
Authenticity
Sentiment
Behavior (each piece of data may someday have its own rules and/or agent(s) that seek to move the data to where it is needed, connect it, maintain it, protect it, improve it, etc.)
Software can become dumber and more generice, yet ultimately be smarter – the smarts moves into the data itself rather than being hard-coded into the software

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.
Data can be shared and linked more easily
Just-in-time schemas – applications can pull the schema for data only when the data is actually needed, rather than having to anticipate it

The Semantic Web = Open database layer for the Web User Profiles Web Content Data Records Apps & Services Ads & Listings Open Data Mappings Open Data Records Open Rules Open Ontologies Open Query Interfaces

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

RDF “Triples”
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 Subject Object Predicate

Semantic Web Data is Self-Describing Linked Data Data Record ID Field 1 Value Field 2 Value Field 3 Value Field 4 Value Definition Definition Definition Definition Definition Definition Definition Ontologies

RDBMS vs Triplestore S P O Person Table f_name jim nova chris lew ID 001 002 003 004 l_name wissner spivack jones tucker Colleagues Table SRC-ID 001 001 001 001 002 002 002 002 003 003 003 003 004 004 004 004 TGT-ID 001 002 003 004 001 002 003 004 001 002 003 004 001 002 003 004 Subject Predicate Object 001 isA Person 001 firstName Jim 001 lastName Wissner 001 hasColleague 002 002 isA Person 002 firstName Nova 002 lastName Spivack 002 hasColleague 003 003 isA Person 003 firstName Chris 003 lastName Jones 003 hasColleague 004 004 isA Person 004 firstName Lew 004 lastName Tucker

Merging Databases in RDF is Easy S P O S P O S P O

Are RDF/OWL the Only Way to Express Semantics?
Other contenders:
String tags
Taxonomies and controlled vocabularies
Microformats
Ad hoc [name, value] pairs
Alternative semantic metadata notations

One Semantic Web or Many?
The answer is….Both
The Semantic Web is a web of semantic webs
Each of us may have our own semantic web…

Why has it Taken So Long?
The Dream of the Semantic Web has been slow to arrive
The original vision was too focused on A.I.
Technologies and tools were insufficient
Needs for open data on the Web were not strong enough
Keyword search and tagging were good enough…for a while
Lack of end-user facing killer apps
Lots of misunderstanding to clear up

Crossing the Chasm…
Communicating the vision
Focus on open data, not A.I.
Technology progress
Standards & tools finally maturing
Needs were not strong enough
Keyword search and tagging not as productive anymore
Apps need better way to share data
Killer apps and content
Several companies are starting to expose data to the Semantic Web. Soon there will be a lot of data.
Market Education
Show the market what the benefits are

Future Outlook
2007 – 2009
Early-Adoption
A few killer apps emerge
Other apps start to integrate
2010 – 2020
Mainstream Adoption
Semantics widely used in Web content and apps
2020 +
Next big cycle: Reasoning and A.I.
The Intelligent Web
The Web learns and thinks collectively

A Mainstream Application of the Semantic Web…

Twine.com Overview
Helps individuals and groups
organize, share and discover
information around their interests .
Instead of social networking, it’s interest networking
Twine is the best service for keeping up with your interests and sharing what interests you with other like-minded people.
Twine will generate a large number of vertical interest portals and attract traffic from search engines and partners
Twine will monetize through advertising, affiliate commerce, sponsorships and subscriptions

Positioning
Facebook - For your relationships
LinkedIn - For your career
Twine - For your interests

Twine Compared to Other Tools
Wikis
Document centric, unstructured data
Everyone sees the same view of the world
Geared towards space (a directory of articles) rather than geared towards time (a sequence of articles)
Users have to do all the work of linking and tagging
No support for social networking or sharing
Only for groups
Blogs
Everyone sees the same view of the world
Geared towards time (a sequence of articles) rather than geared towards space (a directory of articles)
Users have to do all the work of linking and tagging
No support for social networking or sharing
Only for individuals
Twine
Data centric – all data (even unstructured data) becomes structured data
Different views for people with different permissions
Geared towards spacetime – view documents by directory or sequence
Automates tagging, linking and discovery
Built in social networking and sharing
For individuals and groups – a unified framework

Twine is Smart Emails Bookmarks Documents Products Collaborate & Discuss Search & Discover Track Interests Automatically captures & organizes info Recommends relevant things Helps you navigate and search Tags, crawls & links related information People Photos Videos Places Classifieds Notes Events

Let’s take a look at Twine… (demo of Twine site…)

Twine is Powered by The Semantic Web
Twine is built on a new Semantic Web platform
15 patents pending and in process
Easily create new Semantic Web apps
Written in pure Java
Anyone can add & edit ontologies
Scale to manage 10’s of billions of RDF triples
Developer tools and API’s
Open up our platform API’s and open-source in the future
Be the center of the Semantic Web ecosystem

Radar Networks’ Semantic Web Platform SQL Database Web App KnowledgeBase Bookmarklet & Email User Portal REST API SPARQL Relational database RSS Feeds Object Query & Cache Class inferencing Semantic Object TupleStore service SQL Query Generator Predicate Inferencing Tuple Query Access Control WebDAV File Store Flat File Store AJAX, Jetty, PicoContainer, Java, XML, SPARQL Jena, ATOM RDF, OWL RDF, OWL, SQL Mina Postgres, Solaris webDAV, Isilon cluster Cache Remote Access Cache Cache Twine.com Platform Storage Ontology

Differentiation
Focused on sharing knowledge around interests, not just socializing
Smarter than other sites – Twine learns, organizes and recommends automatically
Powered by the Semantic Web – New capabilities are possible
Unified place for all types of information

Target Customer
Twine is for active users of the Web, including consumers and professionals, who create, find and share information about their interests
Interests :
Professional associations
Alumni groups
Social networks (Facebook, Plaxo, LinkedIn)
Volunteer organizations
Groups based on interests (hobbies, health, sports, entertainment, culture, family, technology, user groups, etc.)
Participating/working in teams at organizations of all sizes
Demographics:
18 – 45 years old
Have many personal interests and hobbies
Social connections are important – family, friends, colleagues
Americans with a household income of $100,000 or more
Nearly 26 million such consumers used the Internet in August 2003, spending an average of 27.6 hours online -- more than any other income segment.
Consume an average of nearly 3,000 pages a month, almost 300 pages more than the average Internet user

Market Opportunities for Twine
Individuals
Individual consumers
Individual professionals
Groups, Teams and Communities
Interest communities
Support groups
Content publishers
Users groups
Hobbyists
Social groups
Product communities
Event communities
Communities of practice
Customer support
Collaborative teams

Contact Info
Visit www.twine.com to sign up for the invite beta wait-list
You can email me at [email_address]
My blog is at http://www.mindingtheplanet.net
Thanks!

Rights
This presentation is licensed under the Creative Commons Attribution License.
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

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Spivack Blogtalk 2008

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