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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A Knowledge Based Hybrid Model for Improving Manufacturing System in Rolling Mills


Hot steel rolling is amongst the most important industrial techniques because of huge amount of consumed resources, immense environmental impact, and the significance and enormous quantity of long products. Criteria for improving rolling operations include process efficiency, resource consumption, system reliability, product quality and ergo-ecological sustainability. There is an increasing availability of information within and beyond the domain of forming by rolling. With advances in computerised information processing, it becomes apparent that further progress is to be sought in intelligently combining the strategies and theories developed in differing disciplines. The key to optimising rolling systems is to be found in hybrid models. This approach calls for utilising cross-disciplinary knowledge, including a selection amongst methods such as stochastic, fuzzy and genetic modelling, process control and optimisation as well as supply chain and maintenance management. Evidence obtained by experiments using small-scale chemo-physical modelling encourages the use laboratory rolling for preliminary validations. Research strategy is conceptualised on the basis of a knowledge-based hybrid model. The sample space for this model is constituted by the rolling passes translated into the form of vectors. An example of a rolling pass translation into the vector form is presented.

  • AU
  • GB
  • NZ
  • BA
  • Univ_S_Australia (AU)
Data keywords
  • knowledge
  • knowledge based
Agriculture keywords
  • supply chain
Data topic
  • modeling
  • 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.