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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ARGIS: an Agricultural Resource Geographic Information System for site-specific management of reclaimable saline soils


In this study, an Agricultural Resource Geographic Information System (ARGIS) was developed using oriented-object design and the Microsoft Visual C++ environment. The primary objective of ARGIS was to develop a field-implementable program for site-specific management application in the reclaiming of saline soils. ARGIS includes four main modules: GIS platform, soil sampling, geostatistics analysis, and management zones. In practice, EM38 and GPS were used as data collectors, and soil apparent electrical conductivity (ECa) were measured and received into the ARGIS program with georeferenced information first. Then, the geostatistics analysis model was implemented to describe the spatial variability and to generate the interpolated map of soil properties of interest. Finally, soil properties were selected as the input information using fuzzy-c means unsupervised clustering that assigns field information into potential management zones. Results show that the spatial variability in soil properties was well characterised, and the classified management zones were in favourable agreement with crop yield variability patterns.

  • CN
  • Zhejiang_Univ_ZJU (CN)
Data keywords
  • information system
Agriculture keywords
  • agriculture
Data topic
  • information systems
  • sensors
Document type

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

Institutions 10 co-publis
  • Zhejiang_Univ_ZJU (CN)
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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.