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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An interactive inexact fuzzy bounded programming approach for agricultural water quality management


An interactive inexact fuzzy bounded programming (IFBP) approach is developed through introducing the concept of fuzzy bounded intervals into an interactive fuzzy compromise programming framework. It can provide decision_support for decision makers with conflicting desires of greater objective value and higher safety levels of constraints. In this model, by determining a fuzzy goal associated with different feasibility degrees from a semantic correspondence, the degrees of satisfying each objective can be calculated. Decision makers can intervene in every step of the decision process through analyzing the degrees of approaching the aspiration levels and the risks of violating the constraints. The developed method is applied to an agricultural water quality management case for optimizing planting area, manure/fertilizer application amount, and livestock husbandry size. Results indicated that an increased feasibility degree would correspond to a reduced system benefit. Generally, by analyzing risks of violating the constraints in all solution processes, decision makers who have their own aspiration levels would be able to obtain a balanced solution considering the conflict between satisfying the aspiration levels and minimizing the violation risks. (C) 2013 Elsevier B.V. All rights reserved.

  • CN
  • CA
  • N_China_Elect_Power_Univ (CN)
  • Univ_Regina (CA)
Data keywords
  • semantic
Agriculture keywords
  • agriculture
  • livestock
Data topic
  • information systems
  • modeling
  • decision support
  • semantics
Document type

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

Institutions 10 co-publis
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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.