Difference between revisions of "Knowledge base"
| Line 7: | Line 7: | ||
__TOC__ | __TOC__ | ||
| − | :''For the IT | + | :''For the IT tool that stores and retrieves knowledge, see [[Knowledge repository]]'' |
==Definition== | ==Definition== | ||
Revision as of 19:00, 24 March 2014
Contents
- For the IT tool that stores and retrieves knowledge, see Knowledge repository
Definition
Knowledge base is 1) the knowledge available to an organization 2) the knowledge available in a specific knowledge domain 3) a technology used to store complex structured and unstructured information used by a computer system ( http://en.wikipedia.org/wiki/Knowledge_base Wikipedia)
Summary
Description
Knowledge base
Knowledge assets are those parts of an organization’s intangible assets that relate specifically to knowledge, such as know-how, best practices, and intellectual property. Knowledge assets are often divided into human (people, teams, networks and communities), structural (the codified knowledge that can be found in processes and procedures) and technological (the technologies that support knowledge sharing such as databases and intranets).
By understanding the knowledge assets an organization possesses, the organization can improve its ability to use them to best effect and also identify any gaps that may exist.
Source: Planning and Execution of Knowledge Management Assist Missions for Nuclear Organizations
Computer systems that support knowledge base
Knowledge base is also sometimes used to describe a database of information.
A knowledge-based system is a computer system that is programmed to imitate human problem solving by means of artificial intelligence and reference to a database of knowledge on a particular subject. The purpose of a knowledge base system is to:
- Allow knowledge to be stored and structured;
- Provide an interface with other IT systems that contain knowledge;
- Allow users to find and access knowledge;
- Carry out decision making and problem solving activities to replicate human thought
processes.
In an R&D setting, knowledge base systems can be used to:
- Replace human intervention in some decision-making or trouble-shooting processes in a lab environment (examples include intelligent monitoring/fault diagnosis on large-scale equipment or experiments that require constant supervision);
- Store/preserve knowledge from experts for reuse at a future date (used in conjunction with the knowledge capture techniques described in para 6.2);
- Work faster than human processing for some activities that may require this (examples here include integration with reactor simulator systems to help model rapidly escalating transient situations);
- Assimilate information and integrate with other IT systems such as search engines, document/content management systems, portals and social networking systems as described in Section 6.
Some examples of knowledge base systems are given below, together with the links to the relevant internet sites:
- True knowledge (www.trueknowledge.com). An answer engine capable of answering questions put to it on any topic;
- Solvatio (www.iisy.de). A diagnostic tool, which combines case based reasoning and rules based reasoning together with a self-learning capability;
- Novo (www.novosolutions.com). Help Desk Software, Knowledge Base Software & Service Desk Software Solutions.
Source: Knowledge Management for Nuclear Research and Development Organizations
References
[1]
