{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T05:27:59Z","timestamp":1744349279972},"reference-count":36,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Info. Know. Mgmt."],"published-print":{"date-parts":[[2003,6]]},"abstract":"<jats:p> The acquisition and application of knowledge, in particular tacit knowledge (TK), are seen as decisive competitive factors in the knowledge society of the twenty-first century. Despite much talk about the importance of knowledge transfer, little research shows how to identify and measure TK, less research addresses how to transfer TK between individuals and even fewer of these approaches offer any technology that can assist with transfer. This paper does not address the issues of identification and measurement of TK. The purpose of this paper is two-fold: describe a knowledge acquisition and representation technique, known as Ripple Down Rules (RDR), which can be used to capture knowledge, explicit and tacit, in context from those already identified as experts and to describe a set-theoretical technique, known as formal concept analysis (FCA) to assist transfer of the RDR knowledge to another human. <\/jats:p><jats:p> Unlike most knowledge acquisition approaches, the RDR knowledge acquisition technique does not rely on the expert to specify what they know. Instead, knowledge becomes codified by the RDR system while the domain expert exercises his or her expertise. The approach does not capture all organisational knowledge, but the knowledge that is captured will be a mixture of different types of knowledge, including formal and codified knowledge that can be learnt from a book and practice-based knowledge that is passed on while on the job. The knowledge captured using RDR may be transferred to another individual through the use of FCA to retrospectively and automatically develop knowledge models that the user can explore. This work offers a possible solution to three knowledge management challenges: capture, utilisation and preservation of knowledge within an organisation. <\/jats:p>","DOI":"10.1142\/s0219649203000073","type":"journal-article","created":{"date-parts":[[2003,7,11]],"date-time":"2003-07-11T06:35:02Z","timestamp":1057905302000},"page":"179-190","source":"Crossref","is-referenced-by-count":7,"title":["Acquiring and Applying Contextualised Tacit Knowledge"],"prefix":"10.1142","volume":"02","author":[{"given":"Debbie","family":"Richards","sequence":"first","affiliation":[{"name":"Department of Computing, Division of Information and Communication Sciences, Macquarie University, Sydney, Australia"}]},{"given":"Peter","family":"Busch","sequence":"additional","affiliation":[{"name":"Department of Computing, Division of Information and Communication Sciences, Macquarie University, Sydney, Australia"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-77927-5_12"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(92)90037-X"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1207\/s15516709cog1701_7"},{"key":"rf6","unstructured":"W.\u00a0Clancey, Expertise in context: Human and machine, eds. 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