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 fuzzy-based decision-making procedure for data warehouse system selection


The increase in the number of companies seeking data warehousing solutions, in order to gain significant business advantages, has created the need for a decision-aid approach in choosing appropriate data warehouse (DW) systems. Owing to the vague concepts frequently represented in decision environments, we have proposed a fuzzy multi-criteria decision-making procedure, to facilitate data warehouse system selection, with consideration given to both technical and managerial criteria. The procedure can systematically construct the objectives of DW systems selection to support the business goals and requirements of an organization, and identify the appropriate attributes or criteria for evaluation. In the fuzzy-based method, the weight of each criterion and the rating of each alternative are described using linguistic terms, which can also be expressed as triangular fuzzy numbers. The fuzzy algorithm aggregated the decision-makers' preference rating for criteria, and the suitability of data warehouse alternatives versus the selection criteria, to calculate fuzzy appropriateness indices, through which, the most suitable data warehouse system was determined. A case study of a Bar Code Implementation Project for Agricultural Products in Taiwan was conducted to illustrate this method's effectiveness. (C) 2006 Elsevier Ltd. All rights reserved.

  • TW
  • Natl_Cent_Univ_NCU (TW)
Data keywords
  • data warehouse
Agriculture keywords
  • agriculture
Data topic
  • information systems
  • modeling
  • decision support
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.