Nova Spivack - Semantic Web Talk
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Transcript of Nova Spivack - Semantic Web Talk
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1Radar Networks
Nova SpivackCEO & FounderRadar Networks
Making Senseof the
Semantic Web
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2Radar Networks
About This Talk
•Making sense of the semantic sector
•Making the Semantic Web more useable
• Future outlook
• Twine.com
•Q & A
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3Radar Networks
The Big Opportunity…
The social graph just connects people
People
Groups
The semantic graph connects everything…
EmailsCompanies
Products
Services
Web Pages
Multimedia
Documents
Events
Projects
Activities
Interests
Places
Better search
More targeted ads
Smarter collaboration
Deeper integration
Richer content
Better personalization
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4Radar Networks
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
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5Radar Networks
The Intelligence is in the Connections
Connections between people
Con
nect
ions
bet
wee
n In
form
atio
n
Social Networking
Groupware
JavascriptWeblogs
Databases
File Systems
HTTPKeyword Search
USENET
Wikis
Websites
Directory Portals
2010 - 2020
Web 1.0
2000 - 2010
1990 - 2000
PC Era1980 - 1990
RSSWidgets
PC’s
2020 - 2030
Office 2.0
XML
RDF
SPARQLAJAX
FTP IRC
SOAP
Mashups
File Servers
Social Media Sharing
Lightweight Collaboration
ATOM
Web 3.0
Web 4.0
Semantic SearchSemantic Databases
Distributed Search
Intelligent personal agents
JavaSaaS
Web 2.0 Flash
OWL
HTML
SGML
SQLGopher
P2P
The Web
The PC
Windows
MacOS
SWRL
OpenID
BBS
MMO’s
VR
Semantic Web
Intelligent Web
The Internet
Social Web
Web OS
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6Radar Networks
Beyond the Limits of Keyword Search
Amount of data
Pro
duct
ivity
of S
earc
h
Databases
2010 - 2020
Web 1.0 2000 - 2010
1990 - 2000
PC Era1980 - 1990
2020 - 2030
Web 3.0
Web 4.0
Web 2.0 The World Wide Web
The DesktopKeyword search
Natural language search
Reasoning
Tagging
Semantic Search
The Semantic Web
The Intelligent Web
Directories
The Social Web
Files & Folders
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7Radar Networks
A Higher Resolution Web
ColdplayBand
Palo AltoCity
JanePerson
IBMCompany
DavePerson
BobPerson
DesignTeamGroup
StanfordAlumnae
Group
IBM.comWeb Site
123.JPGPhotoDave.com
Weblog
SuePerson
JoePerson
Dave.comRSS 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
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8Radar Networks
Five Approaches to Semantics
• Tagging
• Statistics
• Linguistics
• Semantic Web
•Artificial Intelligence
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9Radar Networks
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
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10Radar Networks
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
• Lucene
• Autonomy
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11Radar Networks
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…
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12Radar Networks
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
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13Radar Networks
The Artificial Intelligence Approach
• Pros:• Smart in narrow domains• Answer questions intelligently• Reasoning and learning
• Cons:• Computationally intensive• Difficult to scale• Extremely hard to program• Does not work well outside of narrow domains• Training takes a lot of work
• Cycorp
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14Radar Networks
The Approaches Compared
Make the software smarter
Make the Data Smarter
Statistics
Linguistics
SemanticWeb
A.I.
Tagging
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15Radar Networks
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
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16Radar Networks
In Practice: Hybrid Approach Works Best
TaggingSemantic WebTop-downStatisticsLinguisticsBottom-upArtificial intelligence
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17Radar Networks
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
•Apps can become smarter with less work, because the data carries knowledge about what it is and how to use it
•Data can be shared and linked more easily
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18Radar Networks
The Semantic Web = Open database layer for the Web
User
ProfilesWeb
ContentData
RecordsApps &
ServicesAds &
Listings
Open Data Mappings
Open Data Records
Open Rules
Open Ontologies
Open Query Interfaces
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19Radar Networks
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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20Radar Networks
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 ObjectPredicate
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21Radar Networks
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
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22Radar Networks
RDBMS vs Triplestore
S P OPerson Table
f_namejimnovachrislew
ID001002003004
l_namewissnerspivackjonestucker
Colleagues Table
SRC-ID001001001001002002002002003003003003004004004004
TGT-ID001002003004001002003004001002003004001002003004
Subject Predicate Object001 isA Person001 firstName Jim001 lastName Wissner001 hasColleague 002002 isA Person002 firstName Nova002 lastName Spivack002 hasColleague 003003 isA Person003 firstName Chris003 lastName Jones003 hasColleague 004004 isA Person004 firstName Lew004 lastName Tucker
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23Radar Networks
Merging Databases in RDF is Easy
S P OS P O S P O
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24Radar Networks
The Web IS the Database!
Application A Application B
ColdplayBand
Palo AltoCity
JanePerson
IBMCompany
DavePerson
BobPerson
DesignTeamGroup
StanfordAlumnae
Group
IBM.comWeb Site
123.JPGPhotoDave.com
Weblog
SuePerson
JoePerson
Dave.comRSS 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
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25Radar Networks
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
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26Radar Networks
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…
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27Radar Networks
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
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28Radar Networks
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
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29Radar Networks
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
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30Radar Networks
The Future of the Platform…
• 1980’s -- The desktop is the platform
• 1990’s -- The browser is the platform
• 2000’s -- The server is the platform
• 2010’s -- The Web is the platform
• 2020’s -- The network is the platform
• 2030’s -- The body is the platform…?
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31Radar Networks
A Mainstream Application of the Semantic Web…
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32Radar Networks
What is Twine?
• Twine is a new service for managing & sharing information on the Web
•Works for content, knowledge, data, or any other kinds of information
•Designed for individuals and groups that need a better way to organize, search, share and keep track of their information
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33Radar Networks
How Twine Works
1. Collect or author structured or unstructured information into Twine via email, the Web or the desktop
2. Twine creates a knowledge web automatically• Understands, tags & links information automatically• Automatically does further research for you on the Web• Organizes information automatically
3. Provides semantic search, discovery & interest tracking
4. Helps you connect with other people & groups to grow and share knowledge webs around common interests
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34Radar Networks
Use-Cases
•Individuals•Collect & author information about interests•Share with your friends & colleagues•Find and discover things more relevantly
•Groups & Teams•Manage content & knowledge related to common interests, goals, or activities•Leverage and contribute to collective intelligence•Collaborate more productively
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35Radar Networks
Contact Info
•Visit www.twine.com to sign up for the invite beta wait-list
• You can email me at [email protected]
•My blog is at http://www.mindingtheplanet.net
• Thanks!
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36Radar Networks
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