Download - Telework Ontology – needs and solutions
TELEBALT conference "TeleworkinTELEBALT conference "Teleworking Business, Education, Research and g Business, Education, Research and e-Commerce” , Vilnius, Lithuania, Oe-Commerce” , Vilnius, Lithuania, October 21-22, 2002ctober 21-22, 2002
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Telework Ontology – Telework Ontology – needs and solutionsneeds and solutions
Zigmas BigelisZigmas Bigelis Project “TELEBALT” consultant, Project “TELEBALT” consultant, [email protected]@is.lt
ECMConsulting, [email protected] ECMConsulting, [email protected]
Saulius MaskeliūnasSaulius MaskeliūnasInstitute of Mathematics and Informatics, Institute of Mathematics and Informatics, --------------------------
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ContentContent
1. 1. Telework termsTelework terms2. 2. Ontology definitionOntology definition3. 3. Semantic Web Semantic Web 4. Web 4. Web Ontology Ontology LLanguage anguage 5. 5. Taxonomy and ontology softwareTaxonomy and ontology software6. 6. Knowledge ManagementKnowledge Management7. 7. Telework ontology needsTelework ontology needs8. 8. Domain Knowledge CentreDomain Knowledge Centre,, as part of IDC as part of IDC9. 9. Information Demonstration Centre (IDC)Information Demonstration Centre (IDC)10. 10. Ontology-based Web Applications for IDCOntology-based Web Applications for IDC – –
Proposals for PartnershipProposals for Partnership
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1. 1. Telework termsTelework terms
TeleworkTelework TelecommutingTelecommuting Flexible workFlexible work eWorkeWork Remote workRemote work Agile workAgile work TeleworkerTeleworker Mobile workerMobile worker Home-based workerHome-based worker
Virtual teamVirtual team Virtual officeVirtual office HotelingHoteling TelecottageTelecottage TelecentreTelecentre Compressed work Compressed work
scheduleschedule Flexible work programFlexible work program Work-life balanceWork-life balance and much moreand much more
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7. 7. Telework ontology needsTelework ontology needs
Ontology of telework domain itselfOntology of telework domain itself Ontology of teleworker domainOntology of teleworker domain Main telework problems and barriersMain telework problems and barriers
– Management Management – Communication Communication
Both management and communication need for Both management and communication need for better understanding both each other and better understanding both each other and information to be collected, processed and sharedinformation to be collected, processed and shared
Less time for search and retrieval of the relevant Less time for search and retrieval of the relevant informationinformation
2 modes: one knows what knows and don’t knows2 modes: one knows what knows and don’t knows
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2. 2. What is an OntologyWhat is an Ontologywww.cs.ma.ac.uk/~stevensr/onto/node3.html www.cs.ma.ac.uk/~stevensr/onto/node3.html
Ontology is the specification of conceptualization , Ontology is the specification of conceptualization , GruberGruber
The conceptualization is the couching of The conceptualization is the couching of knowledge about the world in terms of entities knowledge about the world in terms of entities (things, the relationships they hold and the (things, the relationships they hold and the constraints between them)constraints between them)
The specification is the representation of this The specification is the representation of this conceptualization in a concrete form. conceptualization in a concrete form.
The main components of an ontology are The main components of an ontology are concepts, relations, instances and axiomsconcepts, relations, instances and axioms
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Ontology-bases applicationOntology-bases applicationssMain areasMain areas
Knowledge management systemsKnowledge management systems E-commerceE-commerce Intelligent search systemsIntelligent search systems
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http://sem.ucalgary.ca/KSI/KAW/KAW99/papers/http://sem.ucalgary.ca/KSI/KAW/KAW99/papers/
Uschold2/final-ont-apn-fmk.pdf Uschold2/final-ont-apn-fmk.pdf
– Neutral authoringNeutral authoring
– Ontology as specificationOntology as specification
– Common access to informationCommon access to information
– Ontology-based search Ontology-based search
Ontology-bases applicationOntology-bases applicationssMain Main typestypes
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3. 3. Semantic WebSemantic Webhttp://www.w3.org/2001/sw/Activityhttp://www.w3.org/2001/sw/Activity
SemanticSemantic comes from the Greek words for comes from the Greek words for signsign, , signifysignify, and , and significantsignificant, and today means , and today means of or of or relating to meaningrelating to meaning, often in language. , often in language.
The Semantic Web is an extension of the current The Semantic Web is an extension of the current Web in which information is given Web in which information is given well-defined well-defined meaningmeaning, better enabling , better enabling computerscomputers and and peoplepeople to work in cooperation. to work in cooperation.
It is the idea of having data on the Web defined It is the idea of having data on the Web defined and linked in a way that it can be used for more and linked in a way that it can be used for more effective discovery, automation, integration, and effective discovery, automation, integration, and reuse across various applications. reuse across various applications.
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Semantic Web (cnt’dSemantic Web (cnt’d 1 1)) http://www.w3.org/2001/sw/Activityhttp://www.w3.org/2001/sw/Activity
For the Web to reach its full potential, it must For the Web to reach its full potential, it must evolve into a Semantic Web, providing a evolve into a Semantic Web, providing a universally accessible platform that allows data to universally accessible platform that allows data to be shared and processed by automated tools as be shared and processed by automated tools as well as by people. well as by people.
The Semantic Web is an initiative of the World The Semantic Web is an initiative of the World Wide Web Consortium (W3C), with the goal of Wide Web Consortium (W3C), with the goal of extending the current Web to facilitate Web extending the current Web to facilitate Web automation, universally accessible content, and automation, universally accessible content, and the 'Web of Trust'.the 'Web of Trust'.
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Semantic Web (cnt’d Semantic Web (cnt’d 22)) http://www.w3.org/2001/sw/Activityhttp://www.w3.org/2001/sw/Activity
Tim Berners-Lee wrote the Road map for the Tim Berners-Lee wrote the Road map for the Semantic Web in 1998, and it continues to be a Semantic Web in 1998, and it continues to be a good place to start for those who enjoy theory good place to start for those who enjoy theory
The Semantic Web lends itself to collaboration, The Semantic Web lends itself to collaboration, teamwork, and cooperation. In addition to the RDF teamwork, and cooperation. In addition to the RDF Interest Group which serves as W3C's primary Interest Group which serves as W3C's primary focal point for Semantic Web community focal point for Semantic Web community discussion, there are a variety of domain specific discussion, there are a variety of domain specific communities who are using RDF/XML to publish communities who are using RDF/XML to publish their data on the Web. their data on the Web.
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4. 4. Web Ontology (WebONT) Web Ontology (WebONT) Working Group CharterWorking Group Charterwww.w3.org/2001/sw/WebOnt/charterwww.w3.org/2001/sw/WebOnt/charter
The WG, part of the Semantic Web Activity, will The WG, part of the Semantic Web Activity, will focus on the development of a language to extend focus on the development of a language to extend the semantic reach of current XML and RDF meta-the semantic reach of current XML and RDF meta-data efforts.data efforts.
Tim Berners-Lee outlined the necessary layers for Tim Berners-Lee outlined the necessary layers for developing of applications that depend on an developing of applications that depend on an understanding of logical content, not just human-understanding of logical content, not just human-readable presentation readable presentation
This WG will focus on building the ontological This WG will focus on building the ontological layer and the formal underpinnings thereof.layer and the formal underpinnings thereof.
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Web Ontology Working GroupWeb Ontology Working Grouphttp://www.w3.org/TR/owl-featureshttp://www.w3.org/TR/owl-features/ /
The OWL (Web Ontology Language) is being The OWL (Web Ontology Language) is being designed by the W3C Web Ontology Working designed by the W3C Web Ontology Working Group in order to provide a language that can be Group in order to provide a language that can be used for applications that need to understand the used for applications that need to understand the content of information instead of just content of information instead of just understanding the human-readable presentation of understanding the human-readable presentation of content. content.
OWL facilitates greater machine readability of web OWL facilitates greater machine readability of web content than XML, RDF, and RDF-S support by content than XML, RDF, and RDF-S support by providing a additional vocabulary for term providing a additional vocabulary for term descriptions.descriptions.
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OWL –ontology definitionOWL –ontology definition
Ontology –Ontology – a machine readable set of a machine readable set of definitions that create definitions that create
a taxonomy of a taxonomy of – classes and classes and – subclassessubclasses, , and and
relationships between themrelationships between them
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OWL (cnt’d)OWL (cnt’d)
Web Ontology language OWL is a semantic Web Ontology language OWL is a semantic markup language for publishing and sharing markup language for publishing and sharing ontologies on the World Wide Web.ontologies on the World Wide Web.
OWL is derived from the DAML+OIL Web OWL is derived from the DAML+OIL Web Ontology Language and builds upon the Resource Ontology Language and builds upon the Resource Description Framework [RDF/XML Syntax]Description Framework [RDF/XML Syntax]
OWL Recommendations to be approved on 2002.OWL Recommendations to be approved on 2002.
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5. 5. Ontology and taxonomyOntology and taxonomy
A taxonomy is a hierarchical system of classification A taxonomy is a hierarchical system of classification representing structural differences representing structural differences http://www.epsltd.com/Database/Reports/Taxonomy/TaxonomyExec.htm http://www.epsltd.com/Database/Reports/Taxonomy/TaxonomyExec.htm
Hierarchical taxonomy expressing IS A (hypernymy Hierarchical taxonomy expressing IS A (hypernymy hyponymy) relation .hyponymy) relation .
By definition, a By definition, a taxonomy taxonomy is simply a classification is simply a classification scheme, whereas an scheme, whereas an ontology ontology serves to provide serves to provide semantics and associations/relationships. semantics and associations/relationships. http://www.brint.com/wwwboard/messages/128417.html http://www.brint.com/wwwboard/messages/128417.html
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Need for Taxonomy Need for Taxonomy
More than 80% of unstructured information on the More than 80% of unstructured information on the Web Web
Cataloguing unstructured information is a chronic Cataloguing unstructured information is a chronic problemproblem
Taxonomy software correlates and groups Taxonomy software correlates and groups unstructured information from myriad of sourcesunstructured information from myriad of sources
Search when you know what are you looking forSearch when you know what are you looking for Search when you don’t knowSearch when you don’t know www.entopia.com/pdfs/delphi_taxonomy_white_paper.pdfwww.entopia.com/pdfs/delphi_taxonomy_white_paper.pdf
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Survey on categorization and Survey on categorization and taxonomy managementtaxonomy management
Survey, February 2002, Delphi GroupSurvey, February 2002, Delphi Group 450 organizations, half of them revenue over %100 million450 organizations, half of them revenue over %100 million More than 60% - finding information was difficult processMore than 60% - finding information was difficult process Over 50% - spending 2 or more hours each day searching Over 50% - spending 2 or more hours each day searching
for informationfor information Search time is one of the fundamental symptoms of infoglut Search time is one of the fundamental symptoms of infoglut
and how to measure taxonomy managementand how to measure taxonomy management Process of search is “waste of time”Process of search is “waste of time” www.entopia.com/pdfs/delphi_taxonomy_white_paper.pdfwww.entopia.com/pdfs/delphi_taxonomy_white_paper.pdf
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Ontology and taxonomy softwareOntology and taxonomy software
Entopya http://www.entopia.com Entopya http://www.entopia.com Applied Semantics Applied Semantics
http://www.aplliedsemantics.com http://www.aplliedsemantics.com Semio http://www.semio.com Semio http://www.semio.com Stanford University project Protégé-2000Stanford University project Protégé-2000 EU projectsEU projects
– On-to-knowledge http://www.ontoknowledge.com On-to-knowledge http://www.ontoknowledge.com – OntoWeb http://www.ontoweb.com OntoWeb http://www.ontoweb.com – and moreand more
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EC project OntoWebEC project OntoWebhttp://www.ontoweb.org/download/deliverables http://www.ontoweb.org/download/deliverables
Ontologies provide a common vocabulary of an area and Ontologies provide a common vocabulary of an area and define-with different levels of formality – the meaning of the define-with different levels of formality – the meaning of the term and the relations between themterm and the relations between them
Knowledge in ontology is mainly formalized using 5 kinds Knowledge in ontology is mainly formalized using 5 kinds of components:of components:– ClassesClasses– RelationsRelations– FunctionsFunctions– AxiomsAxioms– InstancesInstances
Classes in the ontology are usually organized in Classes in the ontology are usually organized in taxonomiestaxonomies
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6. 6. Knowledge Management stagesKnowledge Management stageswww.kmworld.comwww.kmworld.com/publications/publications v11, issue 3 v11, issue 3
Stage 1 – “by the internet out of intellectual Stage 1 – “by the internet out of intellectual capital”. KEY PHRASES : “best practices” and capital”. KEY PHRASES : “best practices” and later “lessons learned”later “lessons learned”
Stage 2 – “human and cultural dimensions, the Stage 2 – “human and cultural dimensions, the human relations stage”. KEY PHRASE: human relations stage”. KEY PHRASE: “communities of practice”“communities of practice”
Stage 3 – “content and retrievability”.KEY Stage 3 – “content and retrievability”.KEY PHRASES : “PHRASES : “CONTENT MANAGEMENTCONTENT MANAGEMENT” and ” and ““TAXONOMIESTAXONOMIES””
Dr. Michael Koenig of Long Island UniversityDr. Michael Koenig of Long Island University
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Creating Knowledge from DataCreating Knowledge from Datahttp://www.darwinmag.com/reada/whitepepaers/070101_data.html http://www.darwinmag.com/reada/whitepepaers/070101_data.html
Transforming data and info into knowledge Transforming data and info into knowledge is not a passive activity such as going to a is not a passive activity such as going to a library and doing some research.library and doing some research.
KM is fundamentally active – people need to KM is fundamentally active – people need to have access to the right info at the right have access to the right info at the right time.time.
KM needs to be proactive, tightly integrated KM needs to be proactive, tightly integrated with business processes and integrally with business processes and integrally related to day-to-day operational activities.related to day-to-day operational activities.
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7. 7. Telework ontology needsTelework ontology needs
Ontology of telework domain itselfOntology of telework domain itself Ontology of teleworker domainOntology of teleworker domain Main telework problems and barriersMain telework problems and barriers
– Management Management – Communication Communication
Both management and communication need for Both management and communication need for better understanding both each other and better understanding both each other and information to be collected, processed and sharedinformation to be collected, processed and shared
Less time for search and retrieval of the relevant Less time for search and retrieval of the relevant informationinformation
2 modes: one knows what knows and don’t knows2 modes: one knows what knows and don’t knows
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Telework ontology needs (cnt’d)Telework ontology needs (cnt’d)
New Telework Consortium New Telework Consortium www.telcoa.orgwww.telcoa.org has been created has been created
Killer application that will drive the growth of Killer application that will drive the growth of ultra-high-bandwidth services to the home ultra-high-bandwidth services to the home won’t be entertainment as is generally won’t be entertainment as is generally assumed, but “telework”, or more assumed, but “telework”, or more specifically what Schaer call “interpersonal specifically what Schaer call “interpersonal communications”communications”
http://www.nwfusion.com.cgi-bin/mailto/x.cgihttp://www.nwfusion.com.cgi-bin/mailto/x.cgi
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8. IDC’s 8. IDC’s Domain Knowledge CentreDomain Knowledge CentreGoal and main featureGoal and main feature
Our goal has been not developing only ontology Our goal has been not developing only ontology but ontology-based Web application and approach but ontology-based Web application and approach (background of methodology) for ontology building(background of methodology) for ontology building
Main feature – from information collected and Main feature – from information collected and enriched by individual during each day work to enriched by individual during each day work to collaborative development of shared knowledgecollaborative development of shared knowledge
Domain Ontology is a core module of knowledgeDomain Ontology is a core module of knowledge
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Domain Knowledge Domain Knowledge
The domain knowledge describes the main The domain knowledge describes the main static information and knowledge objects in static information and knowledge objects in an application domain.an application domain.
The main kind of components used to The main kind of components used to describe domain knowledge is ontologies.describe domain knowledge is ontologies.
http://babage.dia.fi.upm.es/ontoweb/wp1/http://babage.dia.fi.upm.es/ontoweb/wp1/OntoRoadMap/index.html OntoRoadMap/index.html
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Domain Knowledge CentreDomain Knowledge CentreUssage purposesUssage purposes
– collecting informationcollecting information– distributed semi-automatic transforming distributed semi-automatic transforming
information to knowledge and information to knowledge and – shared using of this knowledge and collected shared using of this knowledge and collected
informationinformation– intelligent search of collected information and intelligent search of collected information and
knowledgeknowledge– serving as an information and knowledge serving as an information and knowledge
background for ontology-based applications background for ontology-based applications developmentdevelopment
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Domain Knowledge CentreDomain Knowledge CentreStructureStructure
The core modules:The core modules:
II. Information sources DB, i.e. Domain . Information sources DB, i.e. Domain Knowledge Centre enriched by metadata Knowledge Centre enriched by metadata and metatags (concepts, attributes and and metatags (concepts, attributes and values) values)
IIII. Domain ontology module. Domain ontology module
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I. I. Information sources DB Information sources DB FeaturesFeatures
Enriched info – metatags – are one of Enriched info – metatags – are one of knowledge types in DKCknowledge types in DKC
Knowledge should be created as each day Knowledge should be created as each day procedureprocedure
On the next version adding of knowledge On the next version adding of knowledge should be carried on in shared collaboration should be carried on in shared collaboration modemode
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Information sources DBInformation sources DB – Enter & Edit Form – Enter & Edit Form
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Information sources DB Information sources DB Information representation sInformation representation structure tructure
11stst option option ConceptConcept Property (attribute)Property (attribute) ValueValue Value noteValue note 33rdrd option option ClassClass ConceptConcept Individual (instance)Individual (instance)
22ndnd option option ConceptConcept Property (attribute)Property (attribute) ValueValue Value noteValue note 44thth option option Instance nameInstance name PropertyProperty ValueValue
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55thth option option ClassClass TermTerm -- Definition of termDefinition of term
66thth option option TermTerm Relationship TYPERelationship TYPE Other termOther term CommentComment
Information sources DB Information sources DB Information representation sInformation representation structure (cnt’d)tructure (cnt’d)
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Domain – Concept – Attribute – ValueDomain – Concept – Attribute – Value
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An example of reportAn example of report
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IIII. Domain ontology module. Domain ontology module
Ontology core module is in process of Ontology core module is in process of developmentdevelopment
Network model to be used instead of Network model to be used instead of typically used hierarchical modeltypically used hierarchical model
Ontology module prototype is developed on Ontology module prototype is developed on relational DB (Microsoft Access)relational DB (Microsoft Access)
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Domain ontology moduleDomain ontology moduleOntology development proceduresOntology development procedures
Enriched manually structured information Enriched manually structured information (concepts, attributes, values) serves as a (concepts, attributes, values) serves as a background for developing and continuous background for developing and continuous enhancement of domain ontologyenhancement of domain ontology
Telework ontology contains more than 100 Telework ontology contains more than 100 terms (concepts and attributes)terms (concepts and attributes)
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Domain ontology module Domain ontology module Information representation sInformation representation structuretructure
ClassClass Type of relationType of relation ConceptConcept Type of relationType of relation Property (attribute)Property (attribute) ValueValue Value constraints description Value constraints description
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Enter & Edit Form of Ontology moduleEnter & Edit Form of Ontology module
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9. 9. Information Demonstration CentreInformation Demonstration Centreof TELEBALT Projectof TELEBALT Project
Domain Knowledge CentreDomain Knowledge Centre of Project of Project Activities Activities (telework, teamwork, collaboration) (telework, teamwork, collaboration)
E-library on E-library on EC projects, productsEC projects, products related to related to TELEBALT project using intelligent ontology-TELEBALT project using intelligent ontology-based search based search
E-library on E-library on 66thth Framework Program Framework Program main main issuesissues
Intelligent Search system of TELEBALT Intelligent Search system of TELEBALT websites system (LT, LV, EE)websites system (LT, LV, EE)
Other Other Ontology-based Web applicationsOntology-based Web applications of of TELEBALT project (to be discussed)TELEBALT project (to be discussed)
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Documents (e.g. legal acts) storehouse with Documents (e.g. legal acts) storehouse with ontology-based searchontology-based search
Information collecting and semi-automatic Information collecting and semi-automatic generating of surveys and reportsgenerating of surveys and reports
Website structure ontology – support of Website structure ontology – support of website enhancement and searchwebsite enhancement and search
Management of project groupManagement of project group
10. 10. Ontology-based Web appsOntology-based Web apps for IDC for IDCProposals for PartnershipProposals for Partnership
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Ontology-based Web applicationsOntology-based Web applicationsProposals for Partnership (cnt’dProposals for Partnership (cnt’d 1 1))
Personal and company e-Library Personal and company e-Library Partnership supporting intelligent systemPartnership supporting intelligent system Contracts and project proposals support Contracts and project proposals support
systemsystem Intelligent interactive consulting systemIntelligent interactive consulting system Product and services catalogue Product and services catalogue
development system development system
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Ontology-based Web applicationsOntology-based Web applicationsProposals for Partnership (cnt’d Proposals for Partnership (cnt’d 22))
Information transforming to Knowledge Information transforming to Knowledge systemsystem
Information and Knowledge Quality Information and Knowledge Quality Checking systemChecking system
Integration of Business Intelligence products Integration of Business Intelligence products and Domain ontology and Domain ontology
Ontology-based CRM applicationOntology-based CRM application Document annotation self-automated Document annotation self-automated
generationgeneration
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Ontology-based Web applicationsOntology-based Web applicationsProposals for Partnership (cnt’d Proposals for Partnership (cnt’d 33))
Research and Development information Research and Development information analysis systemanalysis system
Situation evaluation, problem identification, Situation evaluation, problem identification, alternative generation and decision making alternative generation and decision making systemsystem
Training information systems building toolTraining information systems building tool
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Thanks for attention !Thanks for attention !??
Zigmas Bigelis, Zigmas Bigelis, UAB “ECMC” UAB “ECMC”
[email protected] [email protected]
Saulius Maskeliūnas,Saulius Maskeliūnas,Institute of Mathematics and Informatics, VilniusInstitute of Mathematics and Informatics, Vilnius