Semantic Web Research @ UMBC

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Semantic Web Research _at_ UMBC
Dr. Yelena Yesha

• IBM RTP

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About the Semantic Web

• An extension to the present World Wide Web.
• The focus is on enabling computing machines to be
  able to reason about web information in addition
  to display web information.
• NOTE displaying information does not necessarily
  require deep understanding of the information.
• NOTE in order to reason about information often
  requires deep understanding of the information.

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The Current Web
(adopted from Eric Millers presentation
http//www.w3.org/2004/Talks/0120-semweb-umich/)

• Resource
• Identified by URIs
• Untyped
• Links
• href, src
• non-descriptive
• Users
• Exciting world - semanticsof resource, however,
  gleanedfrom content
• Machine
• Very little information available - significance
  of the links only evident fromthe context around
  the anchor

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The Semantic Web
(adopted from Eric Millers presentation
http//www.w3.org/2004/Talks/0120-semweb-umich/)

• Resource
• Globally identified by URIsor locally scoped
  (blank)
• Extensible
• Relational
• Links
• Identified by URIs
• Extensible
• Relational
• Users
• Even more exciting world, richeruser experience
• Machine
• More processable informationis available (Data
  Web)

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The Semantic Web Layer Cake
The Semantic Web will globalize KR, just as the
WWW globalize hypertext -- Tim Berners-Lee
we arehere
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Semantic Web Ontologies

• Formally, an ontology is an explicit
  specification of a conceptualization.
• For the developers, building ontologies is about
  defining shared vocabularies and associated
  semantic relations
• SonyEricsson T68i is a type of cellphone
• All SonyEricsson T68i supports Bluetooth
• Harry has a SonyEricsson T68i device
• gt Harrys cellphone supports Bluetooth.

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Semantic Web Languages

• KR languages for defining ontologies
• W3C Recommendations
• RDF/RDFS -- represents information as N-Triples
  (subject, predicate, object) supports basic
  class-subclass properties.
• OWL (Web Ontology Language) -- adds more vocab.
  for describing classes and properties,
  cardinality, equality, XML datatypes,
  enumerations etc.

http//www.w3.org/2001/sw/
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Semantic Web Research - UMBC

• Team
• Tim Finin
• Anupam Joshi
• Yelena Yesha
• Yun Peng
• 12 Ph.D, 10 M.S students
• Selected Projects
• Swoogle
• Semantic Discovery
• Rei Policies for the Semantic Web
• CoBrA

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An indexing and retrieval engine for the Semantic
Web
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Concepts and Motivation

• Google has made us all smarter
• Software agents will need something similar
  tomaximize the use of information on the
  semantic web.

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Concepts and Motivation

• Semantic web researchers need to understandhow
  people are using the concepts languagesand
  might want to ask questions like
• What graph properties does the semantic web
  exhibit?
• How many OWL files are there?
• Which are the most popular ontologies?
• What are all the ontologies that are about time?
• What documents use terms from the ontology
  http//daml.umbc.edu/ontologies/cobra/0.4/agent ?
• What ontologies map their vocabulary to
  http//reliant.teknowledge.com/DAML/SUMO.owl ?

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Concepts and Motivation

• Semantic web tools may need to find ontologies on
  a given topic or similar to another one.

• UMCPs SMORE annotation editor helps a user add
  annotations to a text document, an image, or a
  spreadsheet.
• It suggests ontologies and terms that may be
  relevant to express the users annotations.
• How can it find relevant ontologies?

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Example Queries and Services

• What documents use/are used (directly/indirectly)
  by ontology X?
• Monitor any ontology used by document X (directly
  or indirectly) for changes
• Find ontologies that are similar to http//
• Let me browse ontologies w.r.t. the
  scienceTopics topic hierarchy.
• Find ontologies that include the strings time
  day hour before during date after temporal event
  interval
• Show me all of the ontologies used by the
  National Cancer Institute

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http//swoogle.umbc.edu/
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SWOOGLE2 Architecture
SWOOGLE 2
Human users
Web Server
SwoogleStatistics
OntologyDictionary
SwoogleSearch
service
Intelligent Agents
Web Service
IR analyzer
SWD analyzer
analysis
SWD Metadata
SWD Cache
digest
SWD Reader
The Web
Candidate URLs
discovery
Web Crawler
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Ontology Dictionary
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Swoogle Statistics
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Semantic Discovery
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Semantic Discovery(2)
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Rei Polices for Open, Distributed and Dynamic
Systems
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Its policies all the way down
1 A robot may not injure a human being, or,
through inaction, allow a human being to come to
harm. 2 A robot must obey the orders given it by
human beings except where such orders would
conflict with the First Law. 3 A robot must
protect its own existence as long as such
protection does not conflict with the First or
Second Law. - Handbook of Robotics, 56th Edition,
2058 A.D.
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Its policies all the way down

• In Asimovs world, the robots didnt always
  strictly follow their policies
• Unlike traditional hard coded rules like DB
  access control OS file permissions
• Autonomous agents need policies as norms of
  behavior to be followed to be good citizens
• So, its natural to worry about
• How agents governed by multiple policies can
  resolve conflicts among them
• How to deal with failure to follow policies
  sanctions, reputation, etc.
• Whether policy engineering will be any easier
  than software engineering

1 A robot may not injure a human being, or,
through inaction, allow a human being to come to
harm. 2 A robot must obey the orders given it by
hu-man beings except where such orderswould
conflict with the First Law. 3 A robot must
protect its own existence as long as such
protection does not conflict with the First or
Second Law. - Handbook of Robotics, 56th Edition,
2058 A.D.
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Our Approach

• Policies are useful at virtually all levels
• OS, networking, data management, applications
• Declarative policies guide the behavior of
  entities in open, distributed environments
• Positive negative authorizations obligations
• Focused on domain actions
• Policies are based on attributes of the action
  (and its actor and target) and the general
  context not just on their identity of the actor

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Rei Policy Language

• Developed several versions of Rei, a policy
  specification language, encoded in (1) Prolog,
  (2) RDFS, (3) OWL
• Used to model different kinds of policies
• Authorization for services
• Privacy in pervasive computing and the web
• Conversations between agents
• Team formation, collaboration maintenance
• The OWL grounding enables policies that reason
  over SW descriptions of actions, agents, targets
  and context

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Rei Policy Language

• Rei is a declarative policy language for
  describing policies over actions
• Reasons over domain dependent information
• Currently represented in OWL logical variables
• Based on deontic concepts
• Permission, Prohibition, Obligation, Dispensation
• Models speech acts
• Delegation, Revocation, Request, Cancel
• Meta policies
• Priority, modality preference
• Policy engineering tools
• Reasoner, IDE for Rei policies in Eclipse

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Rei Specifications (partial)
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Applications past, present future

• Coordinating access in supply chain management
  system
• Authorization policies in a pervasive computing
  environment
• Policies for team formation, collaboration,
  information flow in multi-agent systems
• Security in semantic web services
• Privacy and trust on the Internet
• Privacy in pervasive computing environments

1999
2002
2003
2004
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Example Security and Trust forSemantic Web
Services

• Semantic web services are web services described
  using OWL-S
• Policy-based security infrastructure
• Advantages of using policies
• Expressive -- can be over descriptionsof
  requester, service context
• Authorization Rules for access control
• Privacy Rules for protecting information
• Confidentiality Cryptographiccharacteristics of
  informationexchanged

Policies Semantic Web Services
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Example policies

• Authorization
• Policy 1 Stock service not accessible after
  market closes
• Policy 2 Only LAIT lab members who are Ph.D.
  students can use the LAIT lab laser printer
• Privacy/Confidentiality
• Policy 3 Do not disclose my my SSN
• Policy 4 Do not disclose my home address or
  facts from which it could be easily discovered
• Policy 5 Do not use a service that doesnt
  encrypt all input/output
• Policy 6 Use only those services that required
  an SSN if it is encrypted

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Example

• Mary is looking for a reservation service
• foaf description
• Confidentiality policy
• BravoAir is a reservation service
• OWL-S description
• Authorization policy
• Only users belonging to the same project as John
  can access the service

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Mary

• lt!-- Mary's FOAF description --gt
• ltfoafPerson rdfID"mary"gt
• ltfoafnamegtMary Smithlt/foafnamegt
• ltfoaftitlegtMslt/foaftitlegt
• ltfoaffirstNamegtMarylt/foaffirstNamegt
• ltfoafsurnamegtSmithlt/foafsurnamegt
• ltfoafhomepage rdfresource"http//www.somewebsi
  te.com/marysmith.html"/gt
• ltfoafcurrentProject rdfresource"
  http//www.somewebsite.com/SWS-Project.rdf "/gt
• ltswspolicyEnforced rdfresource"maryConfident
  alityPolicy"/gt
• lt/foafPersongt
• lt/rdfRDFgt

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Bravo Policy

• ltentityVariable rdfabout"bravo-policyvar1"/gt
• ltentityVariable rdfabout"bravo-policyvar2"/gt
• ltconstraintSimpleConstraint
• rdfabout"bravo-policyGetJohnProject"
• constraintsubject"johnJohn"
• constraintpredicate"foafcurrentProject"
• constraintobject"bravo-policyvar2"/gt
• ltconstraintSimpleConstraint
• rdfabout"bravo-policySameProjectAsJohn"
• constraintsubject"bravo-policyvar1"
• constraintpredicate"foafcurrentProject"
• constraintobject"bravo-policyvar2"/gt
• lt!-- constraints combined --gt
• ltconstraintAnd rdfabout"bravo-policyAndCondit
  ion1"
• constraintfirst"bravo-policyGetJohnPro
  ject"
• constraintsecond"bravo-policySameProje
  ctAsJohn"/gt

• ltdeonticRight rdfabout"bravo-policyAccessRigh
  t"gt
• ltdeonticactor rdfresource"bravo-policyvar1"/
  gt
• ltdeonticaction rdfresource"bravo-serviceBrav
  oAir_ReservationAgent"/gt
• ltdeonticconstraint rdfresource"bravo-policyA
  ndCondition1"/gt
• lt/deonticRightgt
• ltrdfDescription rdfabout"bravo-serviceBravoAi
  r_ReservationAgent"gt
• ltswspolicyEnforced rdfresource"bravo-policyA
  uthPolicy"/gt
• lt/rdfDescriptiongt

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How it works
BravoAirWeb service
Mary
URL to foaf desc query request
ltswspolicyEnforced rdfresource
"bravo-policyAuthPolicy"/gt
Matchmaker Reasoner
Bravo Service OWL-S Desc
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How it works
Marys query Bravo Service ? YES
Extract Bravos policy
Does Mary meets Bravos policy ?

• ltdeonticRight rdfabout"bravo-policyAccessRigh
  t"gt
• ltdeonticactor rdfresource"bravo-policyvar1"/
  gt
• ltdeonticaction rdfresource"bravo-serviceBrav
  oAir_ReservationAgent"/gt
• ltdeonticconstraint rdfresource"bravo-policyA
  ndCondition1"/gt
• lt/deonticRightgt
• ltpolicyGranting rdfabout"bravo-policyAuthGran
  ting"gt
• ltpolicyto rdfresource"bravo-policyvar1"/gt
• ltpolicydeontic rdfresource"bravo-policyAcces
  sRight"/gt
• lt/policyGrantinggt
• ltswsAuthorizationPolicy rdfabout"bravo-policy
  AuthPolicy"gt
• ltpolicygrants rdfresource"bravo-policyAuthGr
  anting"/gt
• lt/swsAuthorizationPolicygt
• ltrdfDescription rdfabout"bravo-serviceBravoAi
  r_ReservationAgent"gt
• ltswspolicyEnforced rdfresource"bravo-policyA
  uthPolicy"/gt
• lt/rdfDescriptiongt

Authorization enforcement complete
ltconstraintSimpleConstraint rdfabout
"bravo-policyGetJohnProject
constraintsubject"johnJohn"
constraintpredicate"foafcurrentProject"
constraintobject"bravo-policyvar2"/gt var2
http//www.somewebsite.com/SWS-Project.rdf
BravoAirWeb service
Mary
ltfoafcurrentProject rdfresource
"http//www.somewebsite.com/SWS-Project.rdf"/gt
ltconstraintSimpleConstraint
rdfabout"bravo-policySameProjectAsJohn"
constraintsubject"bravo-policyvar1"
constraintpredicate"foafcurrentProject"
constraintobject"bravo-policyvar2"/gt Is the
constraint true when var2 http//www.somewebsit
e.com/SWS-Project.rdfvar1 http//www.cs.umbc.ed
u/lkagal1/rei/examples/sws-sec/MaryProfile.rdf
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What we learned

• Declarative policies can be used to model
  security, trust and privacy constraints
• Reasonably expressive policy languages can be
  encoded on OWL
• This enables policies to depend on attributes and
  context information available on the semantic web
• Policies are applicable at almost every level of
  the stack, from systems and networking to
  multiagent applications.

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Context Broker Architecture(CoBrA)
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Context Broker Architecture
Pervasive Computing
Semantic Web
CoBrA
Software Agents
CoBrA not CORBA!
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A Birds Eye View of CoBrA
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Key Features of CoBrA

• Using OWL to define ontologies for context
  modeling and reasoning
• Taking a rule based approach to interpret and
  reason about context
• Using a policy language and engine to control the
  sharing of user context

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An EasyMeeting Scenario
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An EasyMeeting Scenario
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Research Work in CoBrA
Context Reasoner
PrivacyProtection
CoBrA Ontologies
EasyMeeting Prototype
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The CoBrA Ontology (v0.4)
http//daml.umbc.edu/ontologies/cobra/0.4/
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Example Location Inference

• Goal reason about a persons location using the
  available sensing information.
• gt Step 1 define a domain spatial ontology

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A Simple UMBC Ontology
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Location Inference
Assume the broker is told that Harry is located
in RM-201A
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Location Inference
A the used spatial relations are
rdfssubProeprtyOf the inRegion property
B inRegion is of type Transitive Property
Based on A B gt
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Other Projects

• Rule ML

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Credits - Current Students

• Harry Chen
• Li Ding
• Sasikanth Avancha
• Pranam Kolari
• Anand Patwardhan
• Rong Pan
• Zhongli Ding
• Olga Ratsimore
• Srikanth Kallurkar
• Sethuram Balaji Kodeswaran
• Jim Parker
• Joel Sachs

• Mathew Baker
• Mohinder Chopra
• Vishal C Doshi
• Shashidhara Ganjugunte
• Abhishek Gujar
• Viral Parekh
• Pavan Reddivari
• Anubhav Sonthalia
• Rong Yu