Capturing Tacit Knowledge in P2P Networks

Encapsulating explicit knowledge within large scale organisations is well understood and several commercial off the shelf applications exist that enable the implementation of efficient knowledge base management systems. This provides the organisation with added value and enables knowledge components to be re-used and freely transferred throughout the organisational enterprise, however a large amount of implicit knowledge is directly unobtainable and often lost when employees leave the organisation. This is known as tacit knowledge and is generally deep routed within the employee’s memory and communicated through face-toface human interactions. The challenge must be to devise indirect mechanisms to extract and represent tacit knowledge using distributed peer-to-peer networks, further enhancing the intellectual capital within the organisation. This paper describes the socio-technical requirements paramount to capturing tacit knowledge using peer-to-peer enabled technologies. We describe the Conceptual Query (ConQue) algorithm and the Knowledge Source Extraction (KeSEn) algorithm and illustrate the functionality of our working model.