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Artificial Memory Semantic Enterprise Innovation Management Scenario DERI GALWAY Galway, September 2004 Lars Ludwig, Xuan Zhou. AM Semantic EIM Scenario Table of Content. Status quo of Enterprise Information Management Ontologizing Enterprise Information Management - PowerPoint PPT Presentation
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Artificial Memory Semantic Enterprise Innovation
Management Scenario
DERI GALWAYGalway, September 2004 Lars Ludwig, Xuan Zhou
Sept. 2004
[email protected] - [email protected]
2
AM Semantic EIM Scenario Table of Content
• Status quo of Enterprise Information Management• Ontologizing Enterprise Information Management• The role of slow- and fast-changing ontology schemes• Personal Knowledge Management• Semantic communication & collaboration• Semantic consolidation and reverse ontology engineering• Enterprise Knowledge Management • Integrated Enterprise Knowledge Management • Steps towards an AM Semantic EIM Scenario
Sept. 2004
[email protected] - [email protected]
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Status QuoEnterprise Information Management and Innovation Management Today
Enterprise Information Management
Maintaining Enterprise Adapting Enterprise
Business Process Management
Performance Management, Business Intelligence
Process / Workflow Management
Traditional Knowledge Management
Idea / Innovation Management
Working ResultDocumentation
Sept. 2004
[email protected] - [email protected]
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Enterprise Information Management
Maintaining Enterprise Adapting Enterprise
Business Process Management
Performance Management, Business Intelligence
Process / Workflow Management
Traditional Knowledge Management
Idea / Innovation Management
Working ResultDocumentation
Status QuoStructured and Unstructured Information in EIM
structured information
unstructured information
Sept. 2004
[email protected] - [email protected]
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Ontologizing EIMReplacing Specific Information and Communication Systems by Semantic Web Technology
Enterprise Information Management
Semantic (Enterprise Knowledge) Web
Innovation Management Ontology
Communication / Collaboration Ontology
(Personal) Knowledge Management Ontology
Strategy & Performance Management Ontology
Process Management Ontology
(Personal) Knowledge Domain Ontologies
Sept. 2004
[email protected] - [email protected]
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Enterprise Information Management
Semantic (Enterprise Knowledge) Web
Innovation Management Ontology
Communication / Collaboration Ontology
(Personal) Knowledge Management Ontology
Strategy & Performance Management Ontology
Process Management Ontology
(Personal) Knowledge Domain Ontologies
Ontologizing EIMSlow-changing and Fast-changing Schemes
slow-changing schemes
fast-changing schemes
Sept. 2004
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Ontologizing EIMCharacteristics of Slow-changing and Fast-changing Schemes
• describe how we (want to) acquire, organize, communicate, exchange, and evaluate information• make information pieces to objects of our acting• can be centrally modelled by classical ontological engineering in a top-down approach due to their stability• can be centrally mapped to each other due to their stability
slow-changing schemes …
• describe the information itself• cannot be centrally modeled due to often quick changes in individual knowledge• cannot be mapped centrally alone - due to individual schema extensions
fast-changing schemes …
Sept. 2004
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Role of Artificial MemoryPersonal Knowledge Management
• AM replaces documents in Knowledge Management thereby providing a single system to manage structured and unstructured information (structured unstructured information)
• The authoring process of information is simplified – no additional annotation process is necessary
• Documents become views on instance entities• The de-normalization of data (duplication in database) can be
prevented
AM
Sept. 2004
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Role of Artificial MemorySemantic Communication / Collaboration
Different persons use their Artificial Memory to …• Synchronously and asynchronously send & receive entities or copies of
entities and groups of entities (instances, concepts, relations, entitiy references) between each other; (manually or automatically) integrate received entities into own AM
• Interlink information bases to allow for seamless inter-AM-browsing• Search in several AMs• Reference entities in other AMs• Collaborative editing, co-browsing• Publish & subscribe entities; notification of new entities, • Export (in different formats) and then send / publish (using different
technology) entities; subscribe & import from different channels
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Sept. 2004
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Role of Artificial MemorySemantic Consolidation
A. Different persons use their Artificial Memory to consolidate their knowledge in a group, departmental or enterprise memory using the same mechanisms as used for semantic communication and semantic collaboration
B. A central organization / instance publishes entities to personal or sub-organizational artificial memories.
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[email protected] - [email protected]
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EKM ScenarioReverse / Bottom-up Ontology Engineering for Fast-changing Schemes
1. A central organization enables AM with basic slow-changing and basic fast-changing schemes
2. Individuals make semantic schema extensions without changing the actual schema (semantic schema mimicking)
3. Individuals evaluate & consolidate semantic extensions by semantic communication and collaboration
4. Extensions are consolidated into, between, and through groups or sub-organizational AMs
5. After thorough evaluation and consolidation, the central schema is being updated and schema changes redistributed
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EKM Scenario EKM enabled by Artificial Memory
1. A (sub-)central organization provides basic knowledge of general importance
2. Individuals acquire or are being provided with new knowledge make extensions to their AM Knowledge Base
3. Individuals evaluate & consolidate knowledge by semantic communication and collaboration
4. Relevant knowledge is consolidated into, between, and through groups or sub-organizational AMs
5. After thorough evaluation and consolidation, the central knowledge base is being updated and generally relevant new knowledge redistributed
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EKM Scenario Integrated EKM
A. It is unlikely that current information systems will be soon and totally replaced by Artificial Memories and Ontology-based technology respectively.
B. Hence it is necessary to integrate present information systems into the scenario / show-case.
C. To distribute and share information a top-down and a bottom-up strategy should be applied likewise.
D. Information in other systems must be made available in hyperlink-able form or as relatable RDF-files in order to avoid unnecessary information duplication.
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DWH
Intranet /Internet
DMS
Web Crawler
CRMERP
Sept. 2004
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EKM Scenario Feedback Loops in Integrated EKM
A. When new information flows into the EKM system, it is important to filter this information. Information has to be evaluated. The information should be aligned to the given knowledge structure. Hence automated information extraction should be ontology-driven. A notification system then can introduce new information available.
B. The use of a feedback / rating ontology should provide semantics to steer the filtering of information in semantic communication and consolidation. In turn, the feedback might improve the extraction that thereby would be driven by both domain and feedback ontology.
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Next StepsHow to proceed? Possible Research Topics and Papers!
Enterprise Information Management
Semantic Enterprise Knowledge Web
Innovation Management Ontology
Communication / Collaboration Ontology
(Personal) Knowledge Management Ontology
Strategy & Performance Management Ontology
Process Management Ontology
(Personal) Knowledge Domain Ontologies PKM and AM
Reverse Ont. Eng.
Sem. Collaboration
Semantic EKM / Web
Integrated SEKM
Semantic iTeams
Semantic (E)IM
Sem. Innovation PM
Semantic Perf.Mgmt.
Semantic BPM
Research Show-Case
HP Use-Case / Ph.D.
Artificial Memory