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Machine-readable encoding for definitions of data required to assess compliance to agr. management and crop production standards.

A report proposing the use of multiple formal ontologies for the collection of compliance data for crop production standards and regulations.

Year of Publication2010

In order to reliably assess compliance to agricultural management and crop production standards and regulations, a large body of data is required. In order that farmers may gather the correct data to self-check compliance, and that they can produce the necessary data in order to prove compliance to controlling bodies, it is desirable, or even essential, that the exact data required be explicitly and unambiguously defined. Although this aim is easily defined, no simple solution is available. Two central problems may be identified: 1. Each standard, or rule within that standard, does not in general explicitly state how compliance should be assessed: often there is no clear single data item, or set of data, which is required, or there may be multiple possible alternatives.2. There is no universal vocabulary or data dictionary for agriculture. Each standard uses its own vocabulary, which may be defined as part of that standard, whilst each FMIS also has an internal data model which may, or more likely may not, correspond to the vocabulary used by any particular standard. Similarly, current data exchange formats for agriculture have a certain vocabulary which does not necessarily correspond to any other. In technical terms, multiple ontologies are in use, which are not always directly comparable.As a proposed partial solution to this complicated problem, a two-stage system is described in this document: a. The machine-readable definition of the rules (FutureFarm Deliverable 4.1.1) reference one or more formal ontologies to specify the concepts which are required to define the rule. b. The FMIS component responsible for evaluating the rules (specified in FutureFarm Deliverable 4.3) provides a mechanism for translating the concepts from the ontologies to a specific data format which is implemented by the FMIS (e.g. agroXML or a software-internal data structure).

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Additional keywords/tags

ffd4 1 2farm management information systems
Organisation Logo for FutureFarm Project

A European project with aims to meet the challenges of the farm of tomorrow by integrating Farm Management Information Systems to support real-time management decisions and compliance to standards.

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