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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Development of an Information Integration and Knowledge Fusion Platform for Spatial and Time based Advisory Services: Precision Farming as a Case Study


One of the most challenging knowledge services is to provide information relevant enough to support making effective decisions in real time. Even though many sources of relevant data and knowledge are available on websites at any given time, they are scattered and offer little or no information on the semantic relationships, thus making such sources hard to exploit. This paper proposes an approach to developing a spatial and time-based advisory system by using ontology for aggregating data from heterogeneous databases, and from devices such as climate sensors and mobile phones, using shallow parsing to extract the domain-specific concepts and their attributes from semi-structured text, and using production rules to activate functional knowledge formalized from natural language text that is dispersed across the Web. Precision farming for rice is used as a case study since it relies upon intensive sensing of environmental conditions of the crop, extensive data handling and processing, and farmer knowledge. This work aims to support resource-poor farmers toward higher productivity while minimizing costs. The service offered is to therefore provide personal assistance, thus enhancing a farmer's ability to apply actions effectively according to the crop calendar; i.e. the optimal use of pesticides and nutrients in heterogeneous field situations that affect crop quality and reduce risk.

  • TH
  • Kasetsart_Univ (TH)
  • Minist_Agr_&_Cooperat (TH)
Data keywords
  • knowledge
  • ontology
  • semantic
Agriculture keywords
  • farming
Data topic
  • information systems
  • semantics
  • sensors
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.