Purpose: This research aimed at identification of issues hindering the full exploitation of ES’s potential in the food safety domain. The gained results served then as a basis for the development of a strategy to overcome existing development hurdles.
Methods: A literature review on ES developed and applied in the domain of food safety was performed covering the period from 2013 to 2015. General structural ES components, stakeholders to-be-involved as well as lessons to-be-learned for ES development were identified from literature reports and own practical experiences.
Results: A key finding of this research is that the proper technical, structural and algorithmic system design addressing the issue of knowledge base updating is crucial for successful ES development. Even though this sounds trivial, evidence from several scientific publications prove that this feature is still not available in many ES. This is caused frequently by the fact that applied knowledge generation algorithms do not support the incremental update of math-based knowledge representation. In the light of this finding we illustrate how the establishment of community driven food safety model repositories could support ES development and which practical steps are needed to develop them.
Significance: Application of ES will become increasingly important in all areas related to food safety. Collaborative efforts to setup shared knowledge repositories have thus a high potential to facilitate math-based knowledge exchange specifically between academia and business and/or governmental institutions. Here we also illustrate that the critical technical and formal foundation for community driven knowledge repositories is already emerging.