Improving the Architecture of Agricultural Knowledge Processing Systems using Design Patterns

Authors

  • Stefan Nadschläger Johannes Kepler University Linz, Institute for Applied Knowledge Processing
  • Jussi Nikander Aalto University, Department of Built Environment
  • Dagmar Auer Johannes Kepler University Linz, Institute for Applied Knowledge Processing

DOI:

https://doi.org/10.17700/jai.2019.1.1.496

Abstract

Use of Knowledge Processing in agriculture has continuously increased, since the first era of knowledge based systems. Such software systems are used for support in detailed tasks, such as determining the amount of fertilizer in precision farming, as well as on high-level decision support, such as ‘what to plant in the next growing season’. Unfortunately, these software systems often have shortcomings in software quality. Applying design patterns is a recognized means to achieve better systems in terms of efficiency, flexibility, and quality. In this paper, several software design patterns are mapped to the context of knowledge processing systems in agriculture. Furthermore, additional patterns are identified and described. The need for patterns with focus on particular aspects of knowledge processing in agriculture is addressed, and an implementation is introduced as a proof of concept.

Author Biography

Stefan Nadschläger, Johannes Kepler University Linz, Institute for Applied Knowledge Processing

Scientific researcher, Institute for Applied Knowledge Processing

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Published

2019-10-01

How to Cite

Nadschläger, S., Nikander, J., & Auer, D. (2019). Improving the Architecture of Agricultural Knowledge Processing Systems using Design Patterns. Journal of Agricultural Informatics, 10(1). https://doi.org/10.17700/jai.2019.1.1.496

Issue

Section

Journal of Agricultural Informatics

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