WIKT Bratislava, 28. november 2006 1
Semantic Organization/Enterprise VisionSemantic Organization/Enterprise Vision
Michal Laclavik, Ladislav Hluchy, Marian Babik, Zoltan Balogh, Ivana Budinska, Martin Seleng
Ústav Informatiky SAV
WIKT Bratislava, 28. november 2006 2
Outline
• Motivation• Processing of Information for Knowledge
Management • Organizational Memories• Semantic based Workflows and Services
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Knowledge Management
• Knowledge is key asset• Employees are coming and going• Needs for managing assets
• Knowledge Management (KM) is the process through which organizations generate value from their intellectual and knowledge-based assets (Source: CIO Magazine)
Characters
Data
Information
Knowledge
Actions
Syntax
Semantics
Pragmatics
Reasoning
(Bergman, 2002, Experience Management)
• Data: 20• Information: 20 oC• Knowledge: room temperature
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Vision of Semantic Web
• The Semantic Web is a mesh of information linked up in such a way as to be easily processable by machines, on a global scale. You can think of it as being an efficient way of representing data on the World Wide Web, or as a globally linked database.
(Source: http://infomesh.net/2001/swintro/ - The Semantic Web: An Introduction)
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Vision of Semantic Organization/Enterprise
• To have all information and data available for computer processing via Semantic Web technology (XML, RDF, OWL)
• Ontology translation not so important on one domain …
• Document and Text analysis results using Semantic annotation are part of this
• Conversion or mapping of RDBMS to XML/RDF/OWL• Active Providing of Information and Knowledge• Workflows of Tasks and Services
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Ontology based Text Annotation - OnTeA
• Detecting Meta data from Text• Preparing improved structured
data for later computer processing• Structured data are based on application ontology
model
Location
Town
isa
Country
isa
skillSQL
Skill
io
skillXML
io
skillPHP
io
JobType
jtPermanent
iohasCountry*
locNewYork
io
locUS
io
JobOffer
job_1_html
io
hasRequirements hasRequirements hasType
hasLocation
hasRequirementshasLocation=>+
Text
Set of Detected individuals
Creating Individual
Individual with properties
Reg. Exp.Ontology
Ontology class
Inference
DomainOntology
Ontology Individual
Ontology annotation
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Objective: Assist user to provide information in context
EMBET: User Assistant
• Collaboration among Users• Knowledge Sharing and Recommendation• Proactive Knowledge Provision• Reuse of Knowledge: Notes, Workflows, Results
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EMBET: Achievements• Software with following
functionality– User Problem description– Displaying Knowledge– Adding Knowledge – Knowledge Reuse– Permanent Notes Storage– Voting on Notes
• EMBET architecture: Core, GUI• Context detection • Context Matching to display
information & knowledge • Plain text analysis using Advanced
Semantic Annotation Algorithms – OnTeA
• Theory of different context matching algorithms
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Presentation of Ontology based Knowledge
• Ontology Tree– Browse window
• Graph– Good for further research
• XSL Transformation– RDF/OWL => Plain XML +
XSL => HTML– Infrastructure to receive plain
XML using XML-RPC
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Similarity Measures
• OntoSim• EMBET• Pellucid
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NAZOU Project
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ACoMA: Emails
• Each organization• Context sensitive• Action Oriented
Email Server
ACoMA Automated Content-
based Message Annotator
Email Client
EMBET Experience
Management based on Text Notes
OM Organizačná pamäť
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Conclusion: Processing of Information for Knowledge Management
• Information context detection• User context detection• Information versus user context matching• Displaying the knowledge
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Knowledge Bases
• Pellucid• NAZOU• K Wf Grid
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PELLUCID
USERS
Pellucid – user interaction
CONTEXT&
ACTIONS
ACTIVEHINTS USER
FEEDBACK
Workflow Tracking/Management System
Pellucid“core”
Pellucid interface
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Knowledge Analysis
• Analysis of Workflows• Case-base Reasoning• Prediction
KAA WS
KAA-Gemini
KAA WXA
Get Workflow ID
Case Base (Memory)
Send Workflow ID & Invoke
Gemini
Retrieve
Workflow
Events
XML Wf DB
Transform to
KA
S and S
tore
Retrieve Cases
Scheduler
AAB
Estimation
Estimation
UAA
Send Workflows &
Results
Workflow History
Portlet (Portal)
Send Data
Result
ElapsedTime
elapsedTime Integer
isa
BinaryResult
hasValue Boolean
isa
owl:Thing
isa
Resource
isa Context
isaCase
isa
WsDeployment
hasURI String
isa
WS.Operation_InvocationContext
hasInputParameter Any*
hasInputResource Instance* Resource
hasWsDeployment Instance WsDeployment
isa
hasWsDeployment
hasInputResource*
hasResult* hasContext*
WeightedFeature
owl:Class
io
io
owl:Thing
io
Profile
hasWeightedFeature Instance* WeightedFeature
isContextConcept Instance owl:Class
isResultConcept Instance owl:Class
io
isa
isa
hasWeightedFeature*
isContextConcept isResultConcept
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K Wf Grid Project
• Semantic Service Oriented Architecture• Workflows of Web Services
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Conclusion
• Semantic Organization/Enterprise Vision• Processing of Info and Knowledge• Knowledge Bases• Semantic Service Oriented Architectures