e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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Expert knowledge-based assessment of farming practices for different biotic indicators using fuzzy logic


The study presented here describes a modeling approach for the ex-ante assessment of farming practices with respect to their risk for several single-species biodiversity indicators. The approach is based on fuzzy-logic techniques and, thus, is tolerant to the inclusion of sources of uncertain knowledge, such as expert judgment into the assessment. The result of the assessment is a so-called Index of Suitability (IS) for the five selected biotic indicators calculated per farming practice. Results of IS values are presented for the comparison of crops and for the comparison of several production alternatives per crop (e.g., organic vs. integrated farming, mineral vs. organic fertilization, and reduced vs. plow tillage). Altogether, the modeled results show that the different farming practices can greatly differ in terms of their suitability for the different biotic indicators and that the farmer has a certain scope of flexibility in opting for a farming practice that is more in favor of biodiversity conservation. Thus, the approach is apt to identify farming practices that contribute to biodiversity conservation and, moreover, enables the identification of farming practices that are suitable with respect to more than one biotic indicator. (C) 2011 Elsevier Ltd. All rights reserved.

  • DE
  • Leibniz_Assoc (DE)
Data keywords
  • knowledge
  • knowledge based
Agriculture keywords
  • farming
Data topic
  • big data
  • modeling
  • semantics
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • Leibniz_Assoc (DE)
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e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.