1Introduction to theSemantic Webexample applicationsITTALKS• ITTALKS is a database driven website of IT related talks at UMBC andother institutions. The database contains information on– Seminar events– People (speakers, hosts, users, …)– Places (rooms, institutions, …)• Web pages with DAML markup are generated• The DAML markup supports agent-based services relating to these talks.• Users get talk announcements based on the interests, locations and schedules.http://ittalks.org/humanviewmachineview2ITTALKS ArchitectureWeb server + Java servletsDAMLreasoningengineDAMLreasoningengine<daml></daml><daml></daml><daml></daml><daml></daml>DAML filesAgentsDatabasesPeopleRDBMSRDBMSDBEmail, HTML, SMS, WAPFIPA ACL, KQML, DAMLSQLHTTP, KQML, DAML, PrologMapBlast, CiteSeer,Google, …HTTPHTTP, WebScrapingWeb ServicesApacheTomcatTravel Agent Game in Agentcitieshttp://taga.umbc.edu/TechnologiesFIPA (JADE, April Agent Platform)Semantic Web (RDF, OWL)Web (SOAP,WSDL,DAML-S)Internet (Java Web Start )FeaturesOpen Market FrameworkAuction ServicesOWL message contentOWL OntologiesGlobal Agent CommunityAcknowledgements: DARPA contract F30602-00-2-0591 and Fujitsu Laboratories of America.Students: Y. Zou, L. Ding, H. Chen, R. Pan. Faculty: T. Finin, Y. Peng, A. Joshi, R. Cost. 4/03MotivationMarket dynamicsAuction theory (TAC)Semantic webAgent collaboration (FIPA & Agentcities)Travel AgentsAuction Service AgentCustomerAgentBulletin BoardAgentMarket Oversight AgentRequestDirect BuyReport Direct Buy Transactions BidBidCFPReport Auction Transactions Report Travel Package Report Contract ProposalWeb Service AgentsOntologieshttp://taga.umbc.edu/ontologies/travel.owl – travel conceptsfipaowl.owl – FIPA content lang.auction.owl – auction servicestagaql.owl – query languageFIPA platform infrastructure services, including directory facilitators enhanced to use DAML-S for service discoveryhttp://ebiquity.umbc.edu/• Our research group’s web site generate both HTML and OWL.• HOW? This is relatively easy since the content is in a database.• PHP is sufficient for the job.•HTML pages have links to corresponding OWL• WHY? This exposes the information to programs and agents – no more web scraping.Mobile & Pervasive Computing Uses3How does OWL Help?servicedescriptionlang.contextmodelinteroplanguagemeta lang(policy)XSLT/XMLfriendly{ PerCom }OWL provided a uniformed language which met many needs in developing a complex pervasive computing system.ontologylanguage•Key Benefits- Helps to separate the task of knowledge engineering and system engineering- Helps to define “semantic” specifications for applications that exploit KR and reasoning- Opens the door to the Semantic Web for mobile and pervasive computing applications ◦ Gaining access to a vast amount of information on the Web ◦ Applications will be less restricted by their sensing capabilityOWL as an Ontology Language•Key benefits- Enables semantic service discovery and matching◦ Expressing more detailed and more precise service description- Provides a means for ubiquitous service composition- Allows intelligent applications to have fine-grain control over system execution◦ E.g. is it economic to print using a close by printer?◦ E.g. is it polite to display my email using the room’s project?OWL as a Service Description Lang.OWL as a Language for Interoperability•Key benefits- Encourages independently developed systems to interoperate◦ A standard language backed up the W3C◦ Industrial organizations tend to follow W3C standards◦ Amateurs tend to develop programs based on W3C standards - Enables knowledge sharing and reasoning◦ APIs for processing RDF/XML -- the normative exchange syntax of OWL -- are widely available and suitable for building commercial strength applications ◦ OWL has well defined language semantics for building OWL reasoners. A few number of OWL reasoners are now available. - Provides standard constructs for ontology mapping ◦ Multiple ontologies will likely to exist in a shared PerCom space◦ Ontology mapping can help apps. that adopt different ontologies to interoperate4OWL is XSLT/XML Friendly• Key benefits- Information expressed in OWL can be transformed into other languages for external processing◦ OWL => Prolog rules or Jess rules◦ OWL => XHTML◦ OWL => PHP, JavaScript- Maximizes the reusability of the knowledge that is encoded in OWL◦ Not all useful tools and applications can process OWL◦ Not all XML developers are willing to switch to OWL◦ Not all users think OWL (esp. in RDF/XML) is easily readableOWL as a Meta Language• Key benefits- Helps to define new languages to control the high level behaviorof a complex system (e.g. policy languages)◦ It’s inflexible to adjust the dynamic behavior of a complex system by writing low level code ◦ Using meta languages, users can change system behavior without needing to change the low-level system implementation- Meta languages (e.g. policy) defined using OWL can be used to work with other knowledge that is expressed in OWL◦ Security -- define policy to control actions that are expressed in OWL◦ Privacy protection -- define policy to protect user private information that are expressed in OWLOWL for Defining Context Model• Key benefits- Helps to overcome semantic ambiguities in representing contexts using programming languages ◦ Java representations of contextual knowledge has limited expressiveness◦ OWL representations have well defined semantics - Encourages the reuse of previously defined context model◦ Generic context models (e.g., time, space, actions, policy) can shared and reused by different context-aware systems◦ Tools (e.g., reasoners, APIs) associated with these generic context models often can also be used by different system implementationsOntology-Driven PerCom SystemsHow Different Systems Use OntologyHow Different Systems Use OntologyXXXEasyMeeting(UMBC)XXXContext Broker Architecture(UMBC)XXTask Computing(Fujitsu)XXXXmyCampus(CMU)XML/XSLT IntegrationEnhance service discoveryDefine Meta-Lang. (Policy)Interop.LanguageContext modeling5CMU MyCampus Project• Objective: Enhance campus life through context-aware services accessible over the WLAN• Ontologies- Personal/contextual: location, calendar, organizational etc.- Privacy preferences: who has access to what, “obfuscation” rules- Web services: automated service identification and access
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