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Journal of Dairy Science Vol. 77 No. 12 3704-3715
© 1994 by American Dairy Science Association ®
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Knowledge Representation Methods for Dairy Decision Support Systems

H. Hogeveen 1, M. A. Varner 1, D. S. Brée 1, D. E. Dill 1, E. N. Noordhuizen-Staseen 1, and A. Brand 1

1 Department of Herd Health and Reproduction, Utrecht University, Yalelaan 7, 3584 CL Utrecht, The Netherlands and Department of Animal Sciences, University of Maryland, College Park 20742 and Computer Science Department, University of Manchester, Manchester M13 9PL, England and Cenex/Land O'Lakes Ag Services, PO Box 64089, Mail Station 670, St. Paul, MN 55164-0089

Knowledge-based systems are currently being applied for decision support systems for management of dairy farms. An important feature in the development and application of knowledge-based systems is the knowledge representation scheme used. Although many knowledge representation schemes are available in artificial intelligence, the existing dairy farm management applications only use production rules. However, the knowledge required for dairy farm management may require other representation schemes, depending on the type of knowledge involved in the decision-making process.

Two classes of knowledge can be distinguished: declarative and procedural (or operational) knowledge. Declarative knowledge is concerned with facts in a domain. Procedural knowledge is knowledge of how to use declarative knowledge. For both types of knowledge, several characteristics can be defined: completeness, certainty, generality, and level. Knowledge representation schemes can be ranked according to their performance on the various knowledge characteristics.

Common schemes for knowledge representation and their strengths and weaknesses are described. Different knowledge representation schemes are illustrated for mastitis and reproductive management.

Key Words: knowledge-based systems • knowledge representation • dairy farm management • decision support systems

Submitted on April 18, 1994
Accepted on July 5, 1994




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W. Steeneveld, L. C. van der Gaag, H. W. Barkema, and H. Hogeveen
Providing probability distributions for the causal pathogen of clinical mastitis using naive Bayesian networks
J Dairy Sci, June 1, 2009; 92(6): 2598 - 2609.
[Abstract] [Full Text] [PDF]


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Copyright © 1994 by the American Dairy Science Association ®.