A key aspect in such scenarios is the realization of so-called organizational memories (OM) which capture, store, distribute, and update relevant enterprise knowledge. Current research in the KnowMore and VirtualOffice projects has been focusing on the integration of formal and non-formal knowledge sources by the use of suitable formal knowledge descriptions and the transformation of informal into formal knowledge. Information retrieval and document analysis and understanding (DAU) have been extended by background knowledge and integrated with process modeling and workflow techniques in order to effectively provide context-specific information for supporting knowledge-work activities.
In order to further develop the KnowMore OM approach towards a real technology the FRODO project tackles the following research questions reflecting the real-world requirements of today's enterprise environments:
Thus, FRODO will provide a flexible, scalable OM framework for evolutionary
Thus, FRODO will provide a comprehensive toolkit for the construction
and maintenance of domain ontologies.
Thus, FRODO will improve information delivery by the OM by developing
more integrated and easier adaptable DAU techniques.
Thus, FRODO will develop a methodology and tool for business-process
oriented knowledge management relying on the notion of weakly-structured
The agent platform shall allow an easy incorporation of new and legacy knowledge sources and services by appropriate wrappers and facilitators. Conceptually, systems realized on top of this agent platform will be a further development of the KnowMore three-layer OM architecture, while technically being instances of Gio Wiederholds Wrapper-Facilitator-Mediator architecture for Information Integration systems.
The coherent design will encompass all modules of the application, the knowledge description, and the knowledge source level, and will provide tailored communication primitives and DAU modules for the OM scenario. This will allow for deeper cooperation and synergies between the manifold sources of formally represented and informal knowledge prevalent in business-process descriptions, ontological structures, user profiles, web-based documents, etc.
Our work will promote the general understanding of enterprise information logistics and will amplify the benefits of Wiederholds approach.
Since all transitions between informal representations and formal inferences are both practically important and scientifically interesting, our classical expertise in document analysis and understanding will be revisited and further developed as a key enabling technology for OM systems. Regarding a systematics of DAU application development, the redesign of DAU functionality in the light of the OM agent framework will lead to a deeper understanding of basic DAU building blocks and their play-together in an application context. Regarding DAU functionality, the close cooperation of DAU components with manifold sources of OM background knowledge, as well as the easy exchange of background knowledge chunks, expectations, intermediary results, user-centric particularities, etc. give possibilities for improving result quality and for envisioning self-adaptive capabilities. By the way, the population of the OM agent platform with existing as well as to-be-developed DAU modules yields a proof-of-concept of the platform's wrapping, representation, and cooperation mechanisms.
While informal documents will be a major source of object level knowledge in an OM, the basis for formal inferences are enterprise information and domain ontologies, the construction and evolution of which is still an open research problem. Pursuing and deepening the approach initiated in KnowMore, we will deliver novel ontology maintenance techniques which extend the manual ontology editing approaches of today by exploitation of text and document analysis in the OM object level as well as feedback from the ontology in use.
All these technical developments constituting a formal and implementation basis of OM systems, will be complemented by appropriate methodological support. All technical developments can only be successful on the basis of a thorough domain and business task analysis of an organization. Moreover, this analysis regards in particular the knowledge-intensive processes which are hard to analyze by nature. Further, such an analysis has to be done in compliance with known and existing modeling endeavors already undertaken in the organization. So we will combine and further develop existing modeling approaches from knowledge engineering, agent-based system development, business-process modeling, and object-oriented system analysis to define a coherent methodology and tool for business-process oriented knowledge management.
Copyright © 1993, 1994, 1995, 1996,
Drakos, Computer Based Learning Unit, University of Leeds.
Copyright © 1997, 1998, Ross Moore, Mathematics Department, Macquarie University, Sydney.
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The translation was initiated by Andreas on 2000-03-28