Brief Resume

Dr. Kiptoo is currently the acting Deputy Director in charge of Management Information Systems (MIS) at the ICT center, University of Nairobi. She has extensive experience in information systems development, sourcing and implementation in both corporate and government institutions. She has worked in different phases of business process automation starting from feasibility studies to systems roll-out and support. She holds a PhD in Information Technology from the University of Pretoria (UP), South Africa and Masters in Applied computing from the University of Nairobi, Kenya.Dr.

Kiptoo C C curriculum vitae



Kiptoo, CC.  2017.  {An ontology and crowd computing model for expert-citizen knowledge transfer in biodiversity management. Study Leaders : Aurona G., Van de Merwe A.}. :200., Number December: University of Pretoria AbstractWebsite

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.


Kiptoo, CC, Gerber A, Van der Merwe A.  2016.  {Towards Citizen-Expert Knowledge Exchange for Biodiversity Informatics: A Conceptual Architecture}. The African Journal of Information and Communication (AJIC). Abstract

This article proposes a conceptual architecture for citizen-expert knowledge exchange in biodiversity management. Expert services, such as taxonomic identification, are required in many biodiversity management activities, yet these services remain inaccessible to poor communities, such as small-scale farmers. The aim of this research was to combine ontology and crowdsourcing technologies to provide taxonomic services to such communities. The study used a design science research (DSR) approach to develop the conceptual architecture. The DSR approach generates knowledge through building and evaluation of novel artefacts. The research instantiated the architecture through the development of a platform for experts and farmers to share knowledge on fruit flies. The platform is intended to support rural fruit farmers in Kenya with control and management of fruit flies. Expert knowledge about fruit flies is captured in an ontology that is integrated into the platform. The non-expert citizen participation includes harnessing crowdsourcing technologies to assist with organism identification. An evaluation of the architecture was done through an experiment of fruit fly identification using the platform. The results showed that the crowds, supported by an ontology of expert knowledge, could identify most samples to species level and in some cases to sub-family level. The conceptual architecture may guide and enable creation of citizen-expert knowledge exchange applications, which may alleviate the taxonomic impediment, as well as allow poor citizens access to expert knowledge. Such a conceptual architecture may also enable the implementation of systems that allow non-experts to participate in sharing of knowledge, thus providing opportunity for the evolution of comprehensive biodiversity knowledge systems.

Kiptoo, CC, Gerber A, van der Merwe A.  2016.  {The ontological modelling of fruit fly control and management knowledge}. Fruit Fly Research and Development in Africa - Towards a Sustainable Management Strategy to Improve Horticulture. Abstract

© Springer International Publishing Switzerland 2016. Fruit fly control and management in Africa has been the topic of several scientific investigations resulting in diverse sources of knowledge on the topic. Despite the existence of this knowledge, frequently it is not readily accessible to all targeted beneficiaries; this can be due to, for example, the remote locations of farms and the complexity of the knowledge. However, recent technological developments such as web technologies and networking allow for the engagement and participation of stakeholder groups in the acquisition and dissemination of knowledge and these technologies can also be applied to fruit fly knowledge. In order to facilitate this stakeholder participation in fruit fly knowledge sharing, the relevant domain knowledge needs to be available in a format that can support stakeholder engagement, preferably through the Web. Fruit fly knowledge has not been modelled in this manner and this paper reports on an investigation to model and capture the relevant domain knowledge using ontologies. The objective of this work is thus the development of the domain ontology and its evaluation using a prototype stakeholder participation system for fruit fly control and management that was capable of utilising the ontology. We describe our findings on the use of ontology technologies for representation of fruit fly knowledge, the fruit fly ontology developed, as well as a prototype Web-based system that uses the ontology as a source of knowledge.


Kiptoo.  2006.  Towards road traffic information system using multi-agents. , Nairobi: University of Nairobi

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