Towards automated compliance checking based on a formal representation of agricultural production standards

Research output: Contribution to journalArticleScientificpeer-review

Researchers

  • Edward Nash
  • Jens Wiebensohn
  • Raimo Nikkilä
  • Anna Vatsanidou
  • Spyros Fountas
  • Ralf Bill

Research units

  • University of Rostock
  • Centre for Research and Technology
  • University of Thessaly

Abstract

Production standards in the form of legal regulations or quality assurance labels are playing an increasingly important role in farming. Each farm must therefore gather information on all standards which apply, which may vary from field-to-field, and ensure that they are respected during operations. This information may be provided on paper or as electronic documents, by the standards publishers or by advisors. Together with the need to document compliance, the need to collect and process the requirements is becoming increasingly burdensome for farmers.

In this paper, two questions are addressed: whether an automation of the compliance checking is possible, in order to assist the farmer by proactively warning against 'forbidden' operations, and how the definition of the production standard may be formally represented in order to clearly and unambiguously inform the farmer as to what is required. This formal representation also forms one of the prerequisites for any automated assessment.

As an initial step, a general model of production standards was developed and applied to some common standards in European agriculture. Based on this model, separating standards into metadata and a list of individual rules (check points), a formal representation was developed and an assessment was made as to whether an automated compliance check was feasible. (C) 2011 Elsevier B.V. All rights reserved.

Details

Original languageEnglish
Pages (from-to)28-37
Number of pages10
JournalComputers and Electronics in Agriculture
Volume78
Issue number1
Publication statusPublished - Aug 2011
MoE publication typeA1 Journal article-refereed

    Research areas

  • Metadata, Ontology language, Rules, Decision support, Knowledge management

ID: 9847657