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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Fancy: An Equine Nutrition and Management Model


Nutrition and management modeling has been expanding rapidly in the last 30 years. Nutrition and physiology models in ruminants have used different modeling techniques ranging from simple empirical-based to mechanistic and dynamic models. The level of complexity is driven by available data and modeler objective. The two primary objectives are to serve as a research tool to help guide future research versus field-applied models. Field-applied models combine empirical and mechanistic techniques, allowing nutritionists and consultants to evaluate and predict animal performance by using inputs that can be collected on-farm and by using standard laboratory methodology. More complex dynamic/mechanistic models have been historically used to guide research. These models have tended to focus on enhancing the biochemical understanding associated with lactating cows. Regardless of methodology, modeling has improved the nutrition and feeding practices of all species in which it has been used. However, limited modeling has occurred regarding the equine. The objectives of this article are to introduce the basis for an equine model (Fancy) and outline how modeling can be used to enhance knowledge by guiding research projects. During the development of Fancy, inconsistencies related to requirement predictions were discovered. Most inconsistencies were related to data limitations; however, this illustrates where modeling can offer significant rewards. The development of a model can assist in defining these inconsistencies and data limitations. Research resources can then be better allocated to address these issues. resulting in expanding the knowledge base of the system being modeled. (C) 2011 Elsevier Inc. All rights reserved.

  • US
    Data keywords
    • knowledge
    • knowledge based
    Agriculture keywords
    • farm
    Data topic
    • modeling
    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.