Rab-KAMS: A Reproducible Knowledge Management System with Visualization for Preserving Rabbit Farming and Production Knowledge

Abstract

The sudden rise in rural-to-urban migration has been a key challenge threatening food security and most especially the survival of Rabbit Farming and Production (RFP) in Sub-Saharan Africa. Currently, significant knowledge of RFP is going into extinction as evident by the drastic fall in commercial rabbit farming and production indices. Hence, the need for a system to proactively preserve RFP knowledge for future potential farmers cannot be overemphasized. To this end, knowledge archiving and management are key concepts of ensuring long-term digital storage of conceptual blueprints and specifications of systems, methods and frameworks with capacity for future updates while making such information readily accessible to relevant stakeholders on demand. Therefore, a reproducible Rabbit production’ Knowledge Archiving and Management System (Rab-KAMS) is developed in this paper. A 3-staged approach was adopted to develop the Rab-KAMS. This include a knowledge gathering and conceptualization stage; a knowledge revision stage to validate the authenticity and relevance of the gathered knowledge for its intended purpose and a prototype design stage adopting the use of unified modelling language conceptual workflows, ontology graphs and frame system. For seamless accessibility and ubiquitous purposes, the design was implemented into a mobile application having interactive end-users’ interfaces developed using XML and Java in Android 3.0.2 Studio development environment while adopting the V-shaped software development model. The qualitative evaluation results obtained for Rab-KAMS based on users’ rating and reviews indicate a high level of acceptability and reliability by the users. It also indicates that relevant RFP knowledge were correctly captured and provided in a user-friendly manner. The developed Rab-KAMS could offer seamless acquisition, representation, organization and mining of new and existing verified knowledge about RFP and in turn contributing to food security.

Authors and Affiliations

Temitayo Matthew Fagbola, Surendra Colin Thakur, Oludayo Olugbara

Keywords

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  • EP ID EP448773
  • DOI 10.14569/IJACSA.2019.0100135
  • Views 85
  • Downloads 0

How To Cite

Temitayo Matthew Fagbola, Surendra Colin Thakur, Oludayo Olugbara (2019). Rab-KAMS: A Reproducible Knowledge Management System with Visualization for Preserving Rabbit Farming and Production Knowledge. International Journal of Advanced Computer Science & Applications, 10(1), 263-273. https://europub.co.uk/articles/-A-448773