1. Semantic Web Research @ UMBC
Dr. Yelena Yesha
Semantic Web UMBC
IBM RTP

2. Semantic Web Research @ UMBC
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.
Yelena Yesha
Semantic Web UMBC

3. Semantic Web Research @ UMBC
The Current Web
(adopted from Eric Miller’s presentation
Resource:
Identified by URI’s
Untyped
Links:
“href”, “src” …
non-descriptive
Users:
Exciting world - semantics of resource, however, gleaned from content
Machine:
Very little information available - significance of the links only evident from the context around the anchor
Yelena Yesha
Semantic Web UMBC

4. Semantic Web Research @ UMBC
The Semantic Web
(adopted from Eric Miller’s presentation
Resource:
Globally identified by URI’s or locally scoped (blank)
Extensible
Relational
Links:
Identified by URI’s
Users:
Even more exciting world, richer user experience
Machine:
More processable information is available (Data Web)
Yelena Yesha
Semantic Web UMBC

5. The Semantic Web Layer Cake
“The Semantic Web will globalize KR, just as the WWW globalize hypertext” -- Tim Berners-Lee
we are here
Yelena Yesha
Semantic Web UMBC

6. 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
=> Harry’s cellphone supports Bluetooth.
Yelena Yesha
Semantic Web UMBC

7. 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.
Yelena Yesha
Semantic Web UMBC

8. 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
Yelena Yesha
Semantic Web UMBC

9. An indexing and retrieval engine for the Semantic Web
Yelena Yesha
Semantic Web UMBC

10. Concepts and Motivation
Google has made us all smarter
Software agents will need something similar to maximize the use of information on the semantic web.
Yelena Yesha
Semantic Web UMBC

11. Concepts and Motivation
Semantic web researchers need to understand how people are using the concepts & languages and 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 ?
What ontologies map their vocabulary to ?
Yelena Yesha
Semantic Web UMBC

12. Concepts and Motivation
Semantic web tools may need to find ontologies on a given topic or similar to another one.
UMCP’s 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 user’s annotations.
How can it find relevant ontologies?
Yelena Yesha
Semantic Web UMBC

13. 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 ‘
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’
Yelena Yesha
Semantic Web UMBC

14. Semantic Web Research @ UMBC
Yelena Yesha
Semantic Web UMBC

15. Semantic Web Research @ UMBC
SWOOGLE2 Architecture
SWOOGLE 2
Web Server
Human users
Swoogle Search
Ontology Dictionary
Swoogle Statistics
service
Web Service
Intelligent Agents
IR analyzer
SWD analyzer
analysis
SWD Cache
SWD Metadata
digest
The updated version
SWD Reader
Candidate
URLs
The Web
discovery
Web Crawler
Yelena Yesha
Semantic Web UMBC

16. Semantic Web Research @ UMBC
Ontology Dictionary
Yelena Yesha
Semantic Web UMBC

17. Semantic Web Research @ UMBC
Swoogle Statistics
Yelena Yesha
Semantic Web UMBC

18. Semantic Web Research @ UMBC
Semantic Discovery
Yelena Yesha
Semantic Web UMBC

19. Semantic Web Research @ UMBC
Semantic Discovery(2)
Yelena Yesha
Semantic Web UMBC

20. Rei – Polices for Open, Distributed and Dynamic Systems
Yelena Yesha
Semantic Web UMBC

21. It’s 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.
Yelena Yesha
Semantic Web UMBC

22. It’s policies all the way down
In Asimov’s world, the robots didn’t 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, it’s 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 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.
Yelena Yesha
Semantic Web UMBC

23. Semantic Web Research @ UMBC
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
Yelena Yesha
Semantic Web UMBC

24. Semantic Web Research @ UMBC
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
Yelena Yesha
Semantic Web UMBC

25. Semantic Web Research @ UMBC
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
Yelena Yesha
Semantic Web UMBC

26. Rei Specifications (partial)
Yelena Yesha
Semantic Web UMBC

27. 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 …
Yelena Yesha
Semantic Web UMBC

28. Example: Security and Trust for Semantic Web Services
Semantic web services are web services described using OWL-S
Policy-based security infrastructure
Advantages of using policies:
Expressive -- can be over descriptions of requester, service & context
Authorization: Rules for access control
Privacy: Rules for protecting information
Confidentiality: Cryptographic characteristics of information exchanged
Policies + Semantic Web Services
Yelena Yesha
Semantic Web UMBC

29. Semantic Web Research @ UMBC
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 doesn’t encrypt all input/output
Policy 6: Use only those services that required an SSN if it is encrypted
Privacy policies and confidentiality policies are very closely related. We currently view privacy policies as restrictions over the input and output of web services. For example, a requester may not want to use a service that asks for his SSN . A more interesting example is when a requester does not want his telephone number to be disclosed. In this case, the reasoner should be able to figure out that given the name and address it is possible to find the user’s telephone number. So the reasoner should restrict access to those services that use the name and address as well as those that use the telephone number directly. This is part of our future work. Confidentiality policies describe the cryptographic protocols required for the input and output of the service.
Yelena Yesha
Semantic Web UMBC

30. Semantic Web Research @ UMBC
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
Yelena Yesha
Semantic Web UMBC

31. Semantic Web Research @ UMBC
Mary
<!-- Mary's FOAF description -->
<foaf:Person rdf:ID="mary">
<foaf:name>Mary Smith</foaf:name>
<foaf:title>Ms</foaf:title>
<foaf:firstName>Mary</foaf:firstName>
<foaf:surname>Smith</foaf:surname>
<foaf:homepage rdf:resource="
<foaf:currentProject rdf:resource=" "/>
<sws:policyEnforced rdf:resource="&mary;ConfidentalityPolicy"/>
</foaf:Person>
</rdf:RDF>
Yelena Yesha
Semantic Web UMBC

32. Semantic Web Research @ UMBC
Bravo Policy
<entity:Variable rdf:about="&bravo-policy;var1"/>
<entity:Variable rdf:about="&bravo-policy;var2"/>
<constraint:SimpleConstraint
rdf:about="&bravo-policy;GetJohnProject"
constraint:subject="&john;John"
constraint:predicate="&foaf;currentProject"
constraint:object="&bravo-policy;var2"/>
rdf:about="&bravo-policy;SameProjectAsJohn"
constraint:subject="&bravo-policy;var1"
<!-- constraints combined -->
<constraint:And rdf:about="&bravo-policy;AndCondition1"
constraint:first="&bravo-policy;GetJohnProject"
constraint:second="&bravo-policy;SameProjectAsJohn"/>
<deontic:Right rdf:about="&bravo-policy;AccessRight">
<deontic:actor rdf:resource="&bravo-policy;var1"/>
<deontic:action rdf:resource="&bravo-service;BravoAir_ReservationAgent"/>
<deontic:constraint rdf:resource="&bravo-policy;AndCondition1"/>
</deontic:Right>
………
<rdf:Description rdf:about="&bravo-service;BravoAir_ReservationAgent">
<sws:policyEnforced rdf:resource="&bravo-policy;AuthPolicy"/>
</rdf:Description>
Yelena Yesha
Semantic Web UMBC

33. How it works BravoAir Web service Mary Matchmaker + Reasoner
URL to foaf desc + query request
<sws:policyEnforced rdf:resource = "&bravo-policy;AuthPolicy"/>
Matchmaker + Reasoner
Bravo Service OWL-S Desc
Yelena Yesha
Semantic Web UMBC

34. Semantic Web Research @ UMBC
How it works
Mary’s query = Bravo Service ? YES
Extract Bravo’s policy
<deontic:Right rdf:about="&bravo-policy;AccessRight">
<deontic:actor rdf:resource="&bravo-policy;var1"/>
<deontic:action rdf:resource="&bravo-service;BravoAir_ReservationAgent"/>
<deontic:constraint rdf:resource="&bravo-policy;AndCondition1"/>
</deontic:Right>
<policy:Granting rdf:about="&bravo-policy;AuthGranting">
<policy:to rdf:resource="&bravo-policy;var1"/>
<policy:deontic rdf:resource="&bravo-policy;AccessRight"/>
</policy:Granting>
<sws:AuthorizationPolicy rdf:about="&bravo-policy;AuthPolicy">
<policy:grants rdf:resource="&bravo-policy;AuthGranting"/>
</sws:AuthorizationPolicy>
<rdf:Description rdf:about="&bravo-service;BravoAir_ReservationAgent">
<sws:policyEnforced rdf:resource="&bravo-policy;AuthPolicy"/>
</rdf:Description>
Does Mary meets Bravo’s policy ?
<constraint:SimpleConstraint
rdf:about = "&bravo-policy;GetJohnProject” constraint:subject="&john;John"
constraint:predicate="&foaf;currentProject" constraint:object="&bravo-policy;var2"/>
var2 =
Authorization enforcement complete
Mary
BravoAir Web service
<foaf:currentProject rdf:resource = "
<constraint:SimpleConstraint
rdf:about="&bravo-policy;SameProjectAsJohn"
constraint:subject="&bravo-policy;var1"
constraint:predicate="&foaf;currentProject"
constraint:object="&bravo-policy;var2"/>
Is the constraint true when var2 = var1 =
The matchmaker first finds all those web services that match Mary’s functional description. In this case, it is only Bravo Service. The matchmaker then extracts Bravo’s authorization policy. It reasons over the authorization policy and Mary’s description to verify that the policy is met. As Mary is in the same project as John, she meets the constraints of the policy.
After this the matchmaker reasons over Mary’s policy in a similar fashion.
Yelena Yesha
Semantic Web UMBC

35. Semantic Web Research @ UMBC
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.
Yelena Yesha
Semantic Web UMBC

36. Context Broker Architecture (CoBrA)
Yelena Yesha
Semantic Web UMBC

37. Context Broker Architecture
Pervasive
Computing
Semantic
Web
CoBrA
Software Agents
CoBrA not CORBA!
Yelena Yesha
Semantic Web UMBC

38. A Bird’s Eye View of CoBrA
Yelena Yesha
Semantic Web UMBC

39. Semantic Web Research @ UMBC
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
Yelena Yesha
Semantic Web UMBC

40. An EasyMeeting Scenario
Alice enters a conference room
Alice “beams” her
policy to the broker B B
The broker builds
the context model
Web
The broker detects
Alice’s presence B
Policy says,
“can share with any
agents in the room” A
Policy says,
“inform my personal
agent of my location” A B
.. isLocatedIn ..
Yelena Yesha
Semantic Web UMBC

41. An EasyMeeting Scenario
The broker tells her
location to her agent A
Her agent informs
the broker of her
role and intentions +
The broker informs
the subscribed agents B
The projector agent
wants to help Alice
The projector agent
asks slide show info. B
The projector agent
sets up the slides
Yelena Yesha
Semantic Web UMBC

42. Semantic Web Research @ UMBC
Research Work in CoBrA
Context
Reasoner
Privacy Protection
CoBrA
Ontologies
EasyMeeting
Prototype
Yelena Yesha
Semantic Web UMBC

43. Semantic Web Research @ UMBC
The CoBrA Ontology (v0.4)
Yelena Yesha
Semantic Web UMBC

44. Example : Location Inference
Goal: reason about a person’s location using the available sensing information.
=> Step 1: define a domain spatial ontology
Yelena Yesha
Semantic Web UMBC

45. Semantic Web Research @ UMBC
A Simple UMBC Ontology
Yelena Yesha
Semantic Web UMBC

46. Semantic Web Research @ UMBC
Location Inference
Assume the broker is told that Harry is located in RM-201A
Yelena Yesha
Semantic Web UMBC

47. Semantic Web Research @ UMBC
Location Inference
A: the used spatial relations are “rdfs:subProeprtyOf” the “inRegion” property
B: “inRegion” is of type “Transitive Property”
Based on A & B => …
Yelena Yesha
Semantic Web UMBC

48. Semantic Web Research @ UMBC
Other Projects
Rule ML
Yelena Yesha
Semantic Web UMBC

49. 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
Yelena Yesha
Semantic Web UMBC