Can you imagine the trouble of searching into something like a file or a document on your computer that has been created a year ago? What is more upsetting is when you can not remember the document name or where among the many storage systems in your local network is your file located. Apart from the worries of where to start searching, you are definitely wasting much of your time into something that is unknown.
However, such troubles can be totally eradicated through metadata browser. With an “intelligent” metadata database that uses knowledge artifacts so that information can be readily located and be made available. Through metadata browser three kinds of searches can be done very conveniently on a knowledge repository. These are: full text searches, metadata searches, and keyword searches. Each knowledge artifact is assigned with specific information that in turn will be used to locate specific details and information. Portal search utilities are also needed.
In full text searches documents are scanned from top to bottom. Words and parts of words are searched and will be matched to the user’s selection. Non-textual information like audios, videos, and graphics seem to be difficult to search though. So the search would be leveled according to appropriateness and relatedness. The tendency would be poor results and more result searches.
Keyword searches employ specific words that are linked with the artifacts identification. The search process is applied manually during the recording of the artifact in the knowledge repository. In most cases, keyword searches produce good but less results. Though the results are also considered more focused compared to full text searches.
Metadata searches on the other hand are derived from pre-defined taxonomy or schematic classification. Through metadata searches, every artifact is recorded based on specific business-defined characteristics. This is considered to be the most excellent form of searching because the taxonomy is already built in the search engine.