The Art of Knowledge
Technological Issues Towards Knowledge-powered Organizations
By: George A. Vouros
Right away the name of the paper grabs me. But as I delved into it it just seemed to be a lot more of the same old terminology thrown around. A lot of theories about theories that sound like they are being copied right out of someone else's book. The ideas of technology and education, or KM, obviously go hand and hand. Are there uphill battles that need to be addressed? Absolutely. Is looking towards the past and quoting what you have been reading for the past year going to get us there? No. There's no exam besides results after all the research has been done.
- Towards this aim, people must work at the "knowledge level": get the right information at the right time and at the right form to perform a task in real time, get connected with colleagues that may provide solutions or hints towards solving problems, form groups of people with different areas of expertise and/or different competencies to achieve a shared goal, be equipped with the necessary applications and data to fulfill their tasks and form decisions in real time. More than that, people should be able to provide feedback and share their knowledge, which must be actively and constantly captured, stored, and organized in the background, so as to be exploited in tasks performance and be disseminated to interested colleagues.
- O'Leary (1998) and others point that the knowledge that an organization stores in its repository may be categorized to be knowledge about proposals that the organization made in the past (proposal knowledge repository), knowledge concerning news about organizations' specific topics (news knowledge repository), knowledge about the best way of doing things within the organization (best practices knowledge repository), and knowledge about peoples competencies within the organization (experts knowledge repository).
- These may be bases exploited by expert systems, formal representations of argumentation structures that record group decision processes, formal representations of business processes, or database schemas. Ontologies (Gruber, 1994; Guarino, 1996) are expected to play an important role here and work towards this aim has already been done: representation ontologies make explicit the commitments for structuring knowledge bases, and therefore a semantics-preservation mapping between different knowledge-base constructs is needed for integration (which in most of the cases is not obvious). Domain ontologies make explicit the conceptualization of a specific domain and can be used for mapping domain concepts from one knowledge base to the other. This is also not trivial, given that different ontologies may provide different conceptualizations of a domain at different levels of granularity, with different organizing principles and different implementation languages
- The focus is on what we think are the key technologies for implementing an organizational memory: collaborative applications with transparent and collaborative interfaces; information integration and ontologies; knowledge representation of business processes and ontologies; and knowledge acquisition, data mining and discovery…. The challenge is great. Not only for designing and developing the key technologies, but also for devising the interplay between the technologies and for supporting the collaboration between the applications themselves, in the context of an active organizational memory system. A paradigm for such interplay of technologies and systems' collaboration is the development of collaborative tools for ontology construction. Such tools involve a number of agents that collaborate among themselves towards the construction of a commonly agreed ontology.
Large repositories of information are great, having a system that involves the user making changes is great (though time consuming and destined to fail due to actual user interaction), the idea of ontologies that overlap and break down the barriers of classification and personalization of information is great. However, nobody has shown me anything on this. No system, other than the roots of autonomous and grid computing have shown me a glimpse of anything more than a marketing strategy in programming/EA clothes.
These appear to be the guidelines slated for the achievement
- the development of frameworks and programming methodologies for the development of collaborative agents;
- the development of ontologies in conjunction with linguistic resources, which will provide the conceptual system and vocabulary for information retrieval and information presentation in multilingual settings;
- the development of standards for integrating heterogeneous information sources and for sharing information between them;
- the synthesis and presentation of information, so it can be delivered and be utilized by different device types; and
- the development of powerful data mining and knowledge discovery tools for dynamically acquiring users' preferences and interests with the minimum user feedback.
Towards the end of the article it did a pretty good job in trying to identify ways in which systems should be drawn to attain, retain, categorize, and make efficient information. It did a nice job of laying a foundation. Oddly enough this is the 50th foundation paper I have read on the topic.
Link posted by JVMM : 3:17 PM