\
 

Start Date

16-8-2018 12:00 AM

Description

Semantic modeling and integration of local indigenous knowledge have become fundamental to improving the degree of accuracy of drought forecasting systems due to the variability of currently used environmental parameters. This research aims to acquire, organize and model natural indicators, behavior and ecological interactions of local indigenous knowledge with a focus on drought forecasting. The data are gathered using qualitative interpretative methodology from the interviews with local farmers and indigenous knowledge expert focus groups. The knowledge is formalised into semantic structure using an ontology for machine readability, reusability, integration, and interoperability with heterogeneous intelligent systems. In this paper, we present the design and development of a domain ontology for the indigenous knowledge on drought. The ontological model is an integral component of the research framework towards the development of semantics-based data integration middleware for local indigenous knowledge and modern knowledge on drought. This research contributes to modeling South African indigenous knowledge on drought into ontological models for use in drought forecasting systems, decision support systems, and expert systems.

Share

COinS
 
Aug 16th, 12:00 AM

IKON-OWL: Using Ontologies for Knowledge Representation of Local Indigenous Knowledge on Drought

Semantic modeling and integration of local indigenous knowledge have become fundamental to improving the degree of accuracy of drought forecasting systems due to the variability of currently used environmental parameters. This research aims to acquire, organize and model natural indicators, behavior and ecological interactions of local indigenous knowledge with a focus on drought forecasting. The data are gathered using qualitative interpretative methodology from the interviews with local farmers and indigenous knowledge expert focus groups. The knowledge is formalised into semantic structure using an ontology for machine readability, reusability, integration, and interoperability with heterogeneous intelligent systems. In this paper, we present the design and development of a domain ontology for the indigenous knowledge on drought. The ontological model is an integral component of the research framework towards the development of semantics-based data integration middleware for local indigenous knowledge and modern knowledge on drought. This research contributes to modeling South African indigenous knowledge on drought into ontological models for use in drought forecasting systems, decision support systems, and expert systems.