The KnowMore Project ( Knowledge Management for Learning Organizations )


Context-Aware, Proactive Delivery of Task-Specific Knowledge



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The KnowMore Project ( Knowledge Management for Learning Organizations ) or Context-Aware, Proactive Delivery of Task-Specific Knowledge



Knowledge Management and Organizational Learning are emerging paradigms in industry

Knowledge Management can be supported by exchange of information

Basically, research on Organizational Memory can concentrate on knowledge explication, or on knowledge capitalization

Practical solutions require different degrees of formalization

The KnowMore approach

One solution approach: Knowledge Management oriented on Business Process Management

Knowledge Management adds a new quality to Business Process Management

Business Process Models represent control flow of business activities

An ideal Knowledge Management system would answer manifold questions related to a given knowledge-intensive activity 

OM technology has to face a number of demanding challenges

Enabling technologies cover the whole cycle of capturing, storage, and utilization of corporate knowledge

KnowMore supports knowledge-intensive tasks (KITs) by active delivery of context-specific information 

Context-specific information supports the user in knowledge-intensive activities

Changes in the process state result in refined support

How to realize such functionalities?

Technical realization (I)

A detailed description of Information Needs extends the process model

Modeling of knowledge-intensive tasks is integrated with business process modeling (BPM)

Preconditions and postprocessing rules of information needs allow to formulate information-seeking strategies

Technical realization (II)

The prototype system illustrates the key players in a workflow scenario (which is an extension to the Workflow Mgt Coalition?s scenario)

The KIT model is processed by the extended worklist handler

Technical realization (III)

The information agent uses formal knowledge to retrieve the information relevant for the task at hand

Post-processing governs the presentation of supporting information

Play-together of formal inferences and background knowledge in the information agent

Purchasing a graphics card example: Find competent employees

Intelligent conceptual information retrieval: search heuristics describe how to navigate in the ontologies

Heuristics specifications are a user-friendly front-end to the KnowMore representation formalism in KIT specifications

Technical realization (IV)

Information retrieval maps information need descriptions to knowledge item descriptions

Ontologies organize information models and background knowledge 

Simplified example of the three information modeling ontologies

Knowledge representation requirements in the area of OM conceptual information retrieval

The KnowMore knowledge representation language: OCRA (object-centered relational algebra)

The OCRA is strictly typed 

OCRA: Annotations allow complex semantic nets to be modeled 

OCRA: Objects have a textual representation

Technical realization (V)

KnowMore fits in the WfMC general workflow system architecture




Technical Realization (VI)

KnowMore envisions a comprehensive toolbox to create the Organizational Memory

(a) The knowledge item description relates OM content to concepts from the domain ontology

(b) The TCW Tool for learning text classification has been integrated to automatically create meta information for text documents in the OM 

The TCW automatically suggests to the user ontological categories as potential indices for text documents

(c) Ontology development: Our approach for acquisition + maintenance is based on automatic thesaurus generation

Documents are a plentiful source of information available in any application domain

The thesaurus generation tool TRex was extended and enhanced

An integrated Ontology/Thesaurus is constructed or updated semi-automatically from the term associations generated by TRex

A first evaluation shows the utility of automatic thesaurus generation techniques for building and maintaining Organizational Memories

The KnowMore ontology editor supports the cumbersome task of ontology construction & maintenance

The user is responsible for the final decision about concepts and link types



The KnowMore research mainly investigated three research areas 

The KnowMore system prototype illustrates key ideas of a three-layered OM approach

KnowMore results spawned several application projects

An OM technology requires further research on all three levels of the KnowMore conceptual architecture

The show goes on ...

Author: DFKI Knowledge Mgt Group 



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