Knowledge transfer has been identified as a strategic process for bridging the persistent gap between theory and practice. In biodiversity management, experts generate different types of knowledge that is transferred to citizen communities for practice. On the other hand, citizens constantly interact with their biosphere and from time to time are requested to convey ground knowledge to the experts for scientific analysis and interpretation. The transfer of knowledge between experts and citizens is faced by different challenges key among them being the large volume of the knowledge, complexity of the knowledge, as well as variegated absorptive capacity among citizen communities. Knowledge transfer models adopted for expert-citizen engagement in the biodiversity management domain must therefore consider these characteristics of the domain. Advances in computing technologies present opportunities to create knowledge transfer models that can minimize these challenges. Current knowledge transfer models were created mainly for organizational knowledge transfer and without consideration of specific computing technologies as a mode of knowledge transfer. These challenges and opportunities highlighted a need to investigate how a technology-based knowledge transfer model for biodiversity management could be created. The focus of this study was to explore enhancement of knowledge transfer in the biodiversity management domain using two specific technologies; knowledge representation using ontologies and crowd computing. The research draws from existing knowledge transfer models and properties of the two technologies. This study assumed the pragmatist philosophical stance and adopted the design science research (DSR) approach which is characterised by two intertwined cycles of ‘build’ and ‘evaluate’. The research produced two main contributions from the two cycles. The build cycle led to creation of a technology-based model for knowledge transfer between experts and citizens in the biodiversity domain and was named the Biodiversity Management Knowledge Transfer (BiMaKT) model. Evaluation cycle resulted in development of a platform for transfer of biodiversity management knowledge between experts and citizens. The BiMaKT model reveals that two technologies; knowledge representation using ontologies and crowd computing, could be synergised to enable knowledge transfer between experts and citizens in biodiversity management. It is suggested that this model be utilised to guide development of biodiversity management applications where knowledge needs to be transferred between experts and citizens. The model also presents opportunity for exploration in other domains, especially where experts and citizens need to exchange knowledge. The knowledge transfer platform, reveals that the BiMaKT model could be used to guide development of biodiversity management knowledge transfer platforms. The study utilises a case of fruit fly control and management knowledge transfer between fruit fly experts and fruit farmers for evaluation of the contributions. An experiment using the case demonstrated that the challenges facing knowledge transfer in the domain could be reduced through ontological modelling of domain knowledge and harnessing of online crowds participation through crowd computing. The platform presents opportunity for more empirical studies on usage of the platform in knowledge transfer activities. / Thesis (PhD)--University of Pretoria, 2017. / Informatics / PhD / Unrestricted