Presentation on theme: "Semantic Web: The Future Starts Today"— Presentation transcript:
1 Semantic Web: The Future Starts Today Industrial Ontologies GroupSemantic Web: The Future Starts Today“Industrial Ontologies” GroupAgora Center, University of Jyväskylä, 23 May 2003
2 “Industrial Ontologies” Group: Our History – We took part in development of the first in USSR Industrial Natural Language Processing System “DESTA”, which included semantic analysis and ontologies;We took part in development of the first in USSR Industrial Automated Natural Language Programming System “ALISA”, which Enabled Semantic Annotation, Discovery and Integration of software components (prototype of today's Semantic Web Services concept);
3 “Industrial Ontologies” Group: Our History – under name of Metaintelligence Lab. we were piloting concept of a Metasemantic Network (triplet-based (meta-)knowledge representation model) – prototype of today’s RDF-based knowledge representation in Semantic Web;– various projects with industrial partners, e.g. MetaAtom – “Semantic Diagnostics of Ukrainian Nuclear Power Stations based on Metaknowledge”; MetaHuman – industrial medical diagnostics expert system based on Metaknowledge”; Jeweler – metamodelling and control of industrial processes, etc.; got several research grants from Finnish Academy;
4 “Industrial Ontologies” Group: Our History – we have created branches in Vrije Universiteit Amsterdam (heart of Semantic Web activities in Europe) where now working 5 our former team members, in Jyvaskyla University (several tens of researchers) and established research groups in Kharkov (Ukraine) on Data Mining, Educational Ontologies, Telemedicine, etc.– we took part in MultiMeetMobile Tekes Project, in InBCT Tekes Project in Tempus EU Compact Project in (or in cooperation with) University of Jyvaskyla where we further promote Semantic Web concepts.
5 Industrial Ontologies Group: Important Objective For us there are no doubts about the possibilities, which Semantic Web opens for industry.that is why one important objective of our activities is to study appropriate industrial cases, collect arguments, launch industrial projects and develop prototypes for the industrial companies to not only believe together with us but also benefit from the Semantic Web.
6 Why and Where Semantic Web ? more then 3,000,000,000 web-pages“Information” burstICT needs comprehensive resource management technologyWWWNeeds for integration of businessesWeb Services for e-BusinessStandardization and Interoperability problemsBusinessKnowledge ManagementConsolidate and reuse experienceStandardize knowledge sharing technologyNeeds for the intelligent tools to use human’s knowledge
7 Approach: Semantic Web “The Semantic Web is a vision: the idea of having data on the Web defined and linked in a way that it can be used by machines not just for display purposes,but for automation, integration and reuseof data across various applications”The Semantic Web is an initiative with the goal of extending the current Web and facilitating Web automation, universally accessible web resources, and the 'Web of Trust', providing a universally accessible platform that allows data to be shared and processed by automated tools as well as by people.
8 Word-Wide Correlated Activities Semantic WebAgentcities is a global, collaborative effortto construct an open network of on-line systemshosting diverse agent based services.Semantic Web is an extension of the currentweb in which information is given well-definedmeaning, better enabling computers and peopleto work in cooperationAgentcitiesGrid ComputingWide-area distributed computing, or "grid” technologies,provide the foundation to a number of large-scale effortsutilizing the global Internet to build distributed computingand communications infrastructures.FIPAFIPA is a non-profit organisation aimedat producing standards for the interoperationof heterogeneous software agents.Web ServicesWWW is more and more used for application to application communication.The programmatic interfaces made available are referred to as Web services.The goal of the Web Services Activity is to develop a set oftechnologies in order to bring Web services to their full potential
10 Web resources / services / DBs / etc. Semantic Web: Resource IntegrationSemantic annotationShared ontologyWeb resources / services / DBs / etc.
11 Semantic Web: What to Annotate ? External world resourcesWeb resources / services / DBs / etc.Web users (profiles, preferences)Shared ontologyWeb agents / applicationsWeb access devicesSmart machines and devices
12 Ontologies: the foundation of Semantic Web Ontologies are key enabling technology for the Semantic Web“..explicit specification of conceptualization..”Ontology is formal and rich way to provide shared and common understanding of a domain, that can be used by people and machinescomment__Thing__AuthorpublicprivateAccess Rightsis-aLocationRelated toDocumentnameReportis-ais-aWeb-pageuriSubjectInstance-ofInstance-ofO. KononenkoV. TerziyanpublicAuthorAccess rightsAuthor#doc1#doc2nameRelated toSemantic WebLocationuriSubjectcomment\\AgServ\vagan\InBCT_1.doccomment3.1: analysisdraftHome pageQuery 1: get all documents from location X, but not web-pagesQuery 2: get documents related to Y, with more then one author, one of which is TerziyanQuery 3: are there web-pages of Z with “private” access related to documents with subject S?
13 Semantic Web: Interoperability Ontology B: ResearchOntology A: DocumentsOntology C: ServicesCommon (shared) ontologySystem 2System 1\\AgServ\vagan\InBCT_1.docV. TerziyanA:ReportA:Location3.1: analysisA:SubjectA:AuthorInstance-ofSemantic WebA:nameA commitment to a common ontology is a guarantee of aconsistency and thus possibility of data (and knowledge) sharing
18 Industrial Ontologies Group Samples of our Research: “Applications of Semantic Web”
19 Web Resource/Service Integration: Server-Based Transaction Monitor ClientwirelessTMWebresource /serviceTransaction ServiceServer
20 Web Resource/Service Integration: Mobile Client-Base Transaction Monitor TMWebresource /servicewirelessClientServerwirelessWebresource /serviceServer
21 The conceptual scheme of the ontology-based transaction management with multiple e-services Terziyan V., Ontological Modelling of E-Services to Ensure Appropriate Mobile Transactions, In: International Journal of Intelligent Systems in Accounting, Finance and Management, J. Wiley & Sons, Vol. 12, 2003, 14 pp.
22 Ontology-Based Transaction Management for the Semantic Web Consider two basic transaction management architectures in mobile environment depending on where the Transaction Monitor (TM) will be located. First one (Server-Based) assumes that TM will be located in server side, e.g. within some transaction management service. Second one (Client-Based) supposes that TM is located in mobile client terminal.The first objective will be to provide and study an integrated mobile transaction management architecture for the Semantic Web applications, which will combine the best features from these two architectures by intelligent switching from one architecture to another one depending on current application context.There is already some ontological support for Semantic Web resources and services interoperability based on OWL, DAML-S. However to be able to manage transactions in Semantic Web across multiple resources (or services) there will not be enough only ontologies for semantic annotations of these resources; there will be evident need of the ontology for the Semantic Web transactions itself.The second objective will be developing pilot ontology for the RDF-based semantic annotation of mobile transactions in the Semantic Web.
23 Architecture for a Mobile P-Commerce Service Terziyan V., Architecture for Mobile P-Commerce: Multilevel Profiling Framework, IJCAI-2001 International Workshop on "E-Business and the Intelligent Web", Seattle, USA, 5 August 2001, 12 pp.
24 BANK: P-Commerce Service provider via resources and users annotations Automatic:Personal ontologyGeneral ontologyMapping and Transactionsvia resources and users annotationsService UserService UserService UserService UserService UserService User
26 Machine-to-Machine Communication P2P ontologyP2P ontologyHeterogeneous machines can “understand” each other while exchanging data due to shared ontologies
27 Semantic Web-Supported Sharing and Integration of Web Services Different companies would be able to share and use cooperatively their Web resources and services due to standardized descriptions of their resources.P2P ontologyP2P ontology
28 Corporate/Business Hub Hub ontologyand shared domain ontologiesPartners / BusinessesCompanies would be able to create “Corporate Hubs”, which would be an excellent cooperative business environment for their applications.What parties can do:What parties achieve:Publish own resource descriptions2 cases:Integration within enterprise (corporation)Integration between separate businessesEverything remains true for both cases, only terms are changedSoftware and data reuseAdvertise own servicesAutomated access to enterprise (or partners’) resourcesLookup for resources with semantic searchSeamless integration of servicesOntologies will help to glue such Enterprise-wide / Cooperative Semantic Web of shared resources
29 Web Services for Smart Devices Smart industrial devices can be also Web Service “users”. Their embedded agents are able to monitor the state of appropriate device, to communicate and exchange data with another agents. There is a good reason to launch special Web Services for such smart industrial devices to provide necessary online condition monitoring, diagnostics, maintenance support, etc."OntoServ.Net"OntoServ.Net: “Semantic Web Enabled Network of Maintenance Services for Smart Devices”, Industrial Ontologies Group, Tekes Project Proposal, March 2003,
30 Global Network of Maintenance Services "OntoServ.Net"OntoServ.Net: “Semantic Web Enabled Network of Maintenance Services for Smart Devices”, Industrial Ontologies Group, Tekes Project Proposal, March 2003,
31 Embedded Maintenance Platforms Embedded PlatformBased on the online diagnostics, a service agent, selected for the specific emergency situation, moves to the embedded platform to help the host agent to manage it and to carry out the predictive maintenance activitiesHost AgentMaintenance ServiceService Agents
32 OntoServ.Net Challenges New group of Web service users – smart industrial devices.Internal (embedded) and external (Web-based) agent enabled service platforms.“Mobile Service Component” concept supposes that any service component can move, be executed and learn at any platform from the Service Network, including service requestor side.Semantic Peer-to-Peer concept for service network management assumes ontology-based decentralized service network management.
33 Industrial Ontologies Group Future Plans: “Applications of Wireless Semantic Web”
34 Semantically annotated personal data Virtually all resources have to be marked with semantic labels that show explicitly themeaning of the resource (piece of data, fact, value etc.) It will make possible for user:To organize own view on data and use it for data managementTo access own and other’s resources with semantic queries using “terms” of own modelTo be able integrate data from other sources(semantics of data is important, data can be converted/translated if needed and appropriate mapping exists)Applications will have:Possibility to discover and operate with user information and preferencesPossibility to share information with applications at other devices and elsewhereMy data description model (ontology)Commondata semantic descriptions (ontologies)mapping between viewsPersonal data-viewSemantic Web Inside™Commitment to ontologyGet ontology of information resources you want to manage as starting point (Design yourself or just download)Extend ontology as you want using visual tools and wizardsUse dynamically generated from ontological description user interface (forms, controls etc.) that provides all means for data access.ApplicationsUser data becomes available to variety ofapplications and other peopleMy resources and their descriptionsOther people’s data-views
35 Modelling of personal data views Simple user data view (as is in most of mobile phones)Data to store in every instance of defined information modelActually, this model is a simple ontology of “Personal Data” domain.Using developed standard ontology languages it will be stored in universal data format.Model of user’s data and other resources:Contacts (phone numbers, names etc.)Notes (some pieces of text)Calendar (with some events assigned)It is rather simple, but a good beginning for own data modelcreation…..
36 Building own data model… added slot (property/field)inherited slot
37 Building own data structure “Relative is a kind of friend”Inherited propertiesLinks to other data entitiesadded slot (property/field)inherited slot
38 Building own data structure Customized data model:new kinds of datanew kinds of representationrules and constraints for data etc.association of data with applicationsadded slot (property/field)inherited slot
39 Using generated interface For described data model forms are generatedData view is described as an ontology which contains all needed information about data structure. User interface is built dynamically from ontology:Fields for dataForm layout, types of controls (e.g. picture, checkboxes etc.)Rules for data that can check some constraints, invoke actions, perform calculations – whatever!
40 Access your data quickly and easily… Possibilities to build flexible, easily customizable data management applications are great.Event dataJust click to openTerziyan’s Contact dataEvery piece of data is somehow described in user’s terms from data-view ontology.Links between data make it easy to find needed information
41 Customizable personal information management environment Easy-to-use, flexible, customizabledata management for usersPersonal data “view”:Development of own view on personal dataReusing of existing views (join, modify, extend)Links between personal and some “global” ontologySharing of data:Applications use data and do it correctly (because of semantics assigned)Applications can exchange data with external sourcesData can be translated in respect of its semantics (for localization, between different data views, to fit some requirements etc.)In such environment even development of own applications/scripts can be possibleOntologies and Semantic Web will enable such kind of applicationsRepositories of ready data-viewsEnabled collaboration and interoperabilityNote: Protégé-2000 ontology development and knowledge acquisition tool was used for demonstration
42 OntoCache Ubiquitous Semantic Web Translation General ontologyUbiquitousSemantic WebTranslationUbiquitous computing seems to penetrate into all human environments. Amount of information resources increases significantly that makes search of appropriate data extremely difficult. This stands even worse for mobile devices which have limited computing resources. Semantic annotation of all such information resources in human environments enhance much the efficiency of their search.Ontocache is a software, capable to process semantically annotated information Web-resources. It provides a local Semantic-based browser of web-resources making their search much easier. Its logic is based on local ontology of the resources the user is interested in. The ontology is used for specification of semantic queries that are sent by software to the external environment. The interface of the browser can combine tree-based navigation with semi-natural queries. Initially some statistically general ontology is set as default in the mobile terminal. However, user can alter it according to his needs (student, doctor, psychologist, etc.).If the local ontology isn’t detailed enough for composition of a final query its deeper parts are downloaded from external stores. Thus, depending on user preferences some parts of local ontology with time die and some extend. Shared ontologies make the queries and resources descriptions be based on common vocabularies.Semantic annotations of Web-services (or any other resources) based on shared ontologies enhance much the efficiency of their search/browsing from the PDA. Local ontology adapts permanently to the user preferences.Personalontology
43 OntoCache: benefitsContext and preferences-based adaptationSupport for semi-natural queriesEffective filtering of wide variety of Web-resourcesTechnology that supports future Ubiquitous Semantic WebOntoCache is a tool that conforms with future vision of having all information resources semantically annotated. The benefits it gives correspond to the main promise of Semantic Web technology to provide effective filtering in conditions of information burst. The idea takes into account limited computing resources of mobile devices and assumes adaptation of local ontology to the user preferences. Caching of ontology allows decreasing the data traffic in the form of external parts of ontologies.Semantic data facilitates much more complicated queries than keyword-based ones – semi-natural.Additionally, the behaviour of the navigator can be context-dependent (location, weather, daylight personalization, etc.)
44 Agent-to-Agent communication Peer-to-PeerSemantic annotation of the local data enables its intelligent processing by software. Ontologies provide interoperability between heterogeneous peers.Phone calls are also possible between mobile terminal agents. They are performed without human participation in order to exchange local information.
45 Agent-to-Agent communication semantics enablesintelligent data processingontological relationsBusinessdefine possibleCookingcooperation betweendomain agentsshared ontologyHealthensuresinteroperabilityWhatever?Semantic enriching mobile device data allows software agents perform its intelligent processing substituting human. Software agents which had been programmed basing on certain ontology can perform domain-specific data processing. Relations between domain ontologies define possible cooperation patterns between correspondent agents. Shared ontology ensures interoperability between agents that exchange information.annotate problem domainsinto related ontologiesprogramm softwarebasing on the ontologiessemantically enrichdata basing on ontologies
46 Telemedicine Health Maintenance without barriers Anytime and Anywhere Cases of “Human Maintenance” ActivitiesInteraction“Recovery” Agents“Diagnostic” Agents“Platform Steward”“WatchDog”“Therapist”Human andLocal Health Maintenance CenterRemote Health Maintenance CenterMaintenance Crew ServiceHealth CenterOn a beachAt universityAnywhereHealth Maintenancewithout barriersFishingAnytime and AnywhereIn the officeOutside
47 OntoGames: New Games Generation Personal ontologyGeneral ontologyPersonal User ProfileCommon Games ProfilePUPCGPone LIFE - many ROLESPersonal Reality into each game
48 OntoGames: Semantic Games Space Personal ontologyGeneral ontologySemantical Games Spaceone LIFE - one GAMEReal Life - part of the gameone game - many roles
49 OntoGames: Exit in the Real Life Personal ontologyGeneral ontologyNon Stop Game - Non Stop LifeOntoGamesCONNECTING PEOPLEGame - exit in the Real LifeReality connectionvia the gameReality connectionvia the game
50 BANK: Data annotationIn order to make miscellaneous data gathered and used later for some processing,every piece of data needs label assigned, which will denote its semantics in terms ofsome ontology. Software that is developed with support of that ontology can recognize the data and process it correctly in respect to its semantics.Annotated data (RDF)Ontology of gathered dataWeb forms and dialogs generatedProcessing of data by some other semantic-aware applications
51 BANK: Customer’s data processing ClientsClients clusteringInput formsDataStorageBankClientsOntologyIntelligentontology-basedsoftware
52 BANK: Services annotation Semantically annotated bank servicesI want to …Information filing, all documentation and transactionsLess detailed informationAgent-assistantCustomerSemantics enabled services – easy way to use for customer
53 BANK: Loan Borrower annotation Bank - investorLoan borrowersAutomated support of:making decisions about trustingprediction of future trendsvia semantically annotated loan borrowers information
54 Read Our Recent Reports Semantic Web: The Future Starts Today(collection of research papers and presentations of Industrial Ontologies Group for the Period November 2002-April 2003)Semantic Web and Peer-to-Peer: Integration and Interoperability in IndustrySemantic Web Enabled Web Services: State-of-Art and ChallengesDistributed Mobile Web Services Based on Semantic Web: Distributed Industrial Product Maintenance SystemAvailable online in:V. TerziyanA. ZharkoO. KononenkoO. KhriyenkoIndustrial Ontologies Group
55 Semantic Web: The Future starts today Interoperability standardse-Business,net-marketsEnterprise ApplicationIntegrationWeb-services“Web Of Trust”
56 Industrial Ontologies Group: Examples of Related Contacts
57 University of Jyvaskyla Experience: Examples of Related Courses
58 Cooperation with American Universities John CannyProfessor,Division of Computer Science, University of California, Berkeley, USAIoannis Kakadiaris Ass. Professor, Department of Computer Science, University of Houston, USAIoannis is the founder and Director of Visual Computing Laboratory and the Director of the Division of Bioimaging and Biocomputation at the UH Institute for Digital Informatics and Analysis. He is the recipient of a year 2000 NSF Early Career Development Award.John came from MIT in 1987 after his thesis on robot motion planning, which won the ACM dissertation award. He received a Packard Foundation Fellowship and a PYI while at Berkeley. He developed inexpensive, ubiquitous telepresence robots called "PRoPs”...Cooperation focuses to investigating issues related to management of the Web content which includes human motions as its component, according to the common framework of management multimedia content in the Semantic Web. Possible applications considered:- Automatic remote camera control (behavior recognition, intentions capture, operator (astronaut) actions control etc.)- Semantic video transmission (transmit wireless only recognized semantics of motions).Cooperation focuses to following subjects:- Knowledge management of a community of trust;- Collaborative Filtering with Privacy;- Intelligent Integration of Filtering Models;- Adaptive User Interfaces;- Human-Centered Computing;- Online Collaborative learning.
59 ConclusionSemantic Web is not only a technology as many used to name it;Semantic Web is not only an environment as many naming it now;Semantic Web it is a new context within which one should rethink and re-interpret his existing businesses, resources, services, technologies, processes, environments, products etc. to raise them to totally new level of performance…Contact: Vagan Terziyan(tel )