Abstract
Arable farmers and their suppliers, consultants and procurers are increasingly dealing with gathering and processing of large amounts of data. Data sources are related to mandatory and voluntary registration (certification, tracing and tracking, quality control). Besides data collected for registration purposes, decision support systems for strategic, tactical and operational tasks yield enormous amounts of mainly digital information. Data of similar nature but with often varying definitions are collected and processed separately for different purposes. This paper describes for an important arable crop - the processing potato - which data requirements and flows exist at present and how they could possibly be described in a unifying ontology. An ontology describes the concepts, attributes and relations in a specific knowledge domain using a standardized representation language. Important concepts in this domain are for example crop, parcel, soil, treatment and farm. The ontology - once elaborated - will reduce the overlap between information models and helps to overcome the problem of data definition and representation. It is a key element for the development of systems that can automatically learn either with the help of expert knowledge or through adequate numerical techniques.
Original language | English |
---|---|
Pages (from-to) | 177-201 |
Journal | Potato Research |
Volume | 49 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2006 |
Keywords
- Certificate
- Crop growth model
- Database management
- Decision support system
- Ontology
- Potato
- Registration
- Self-learning system