University of Nottingham Malaysia
School of Computer Science
     
  

CropBase Scholarship: Ontology-driven crop base knowledge system

CFFRCPLUS SCHOLARSHIP SCHEME

CROPBASE PROGRAMME

Project Title

Ontology-driven crop base knowledge system

Project Description

The aim of this project is to combine and expand existing crop ontologies and if needed modify them to ensure consistency, include data for underutilised crops (e.g., Bambara groundnuts), and provide support for decision making by crop growers in selecting suitable crops for their circumstances, including the type of land and climate, likely plant diseases, pests and other problems, and implement a web tool to provide this support with an ontology in the background. It is part of a multidisciplinary research project, so other crop data required for this project will be obtained from other collaborative research projects.

We represent knowledge in Web Ontology Language (OWL) which extends RDF and RDFS and which has been developed as an ontology language that defines classes and properties and their relationships. The World Wide Web Consortium (W3C) has declared two different standards for OWL, namely, OWL 1 and OWL 2. We use OWL 2, which is based on description logic (DL), a decidable fragment of first order logic that is used for efficient and tractable reasoning. The resulting tool will use the ontology as the main knowledge source for answering user queries, but will also involve an additional rule-based decision support mechanism which will ask for information about the concrete parameters relevant for the crop grower and display information about suitable crops in the form which is precise but easy to understand for non-computer scientist. In technical terms, the tool is a hybrid system which uses both ontology definitions and rules.

The successful candidate will have a strong background in computer science and must have excellent programming skills (particularly Java), a sound knowledge of ontology. Some knowledge of, or interest in, rule-based reasoning and/or AI techniques, would be desirable.The successful candidate will collaborate with other CFFRC researchers.

Level: PhD

Supervisor names and contact details:

  1. Abdur Rakib, School of Computer Science, UNMC (Abdur.Rakib@nottingham.edu.my)
  2. Natasha Alechina, School of Computer Science, UoN (Natasha.Alechina@nottingham.ac.uk)

Posted on 17th December 2012

School of Computer Science

University of Nottingham Malaysia
Jalan Broga, 43500 Semenyih
Selangor Darul Ehsan
Malaysia

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