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.

You can access and play with the graphs:

Discover all records
Home page


SWMRD: a Semantic Web-based manufacturing resource discovery system for cross-enterprise collaboration


As supply chains are becoming ever more global and agile in the modern manufacturing era, enterprises are increasingly dependent upon the efficient and effective discovery of shared manufacturing resources provided by their partners, wherever they are. Enterprises are thus faced with increasing challenges caused by the technical difficulties and ontological issues in manufacturing interoperability and integration over heterogeneous computing platforms. This paper presents a prototype intelligent system SWMRD ( Semantic Web-based manufacturing resource discovery) for distributed manufacturing collaboration across ubiquitous virtual enterprises. Ontology-based annotation to the distributed manufacturing resources via a new, multidisciplinary manufacturing ontology is proposed on the semantic web to convert resources into machine understandable knowledge, which is a prelude to the meaningful resource discovery for cross-enterprise multidisciplinary collaboration. An ontology-based multi-level knowledge retrieval model is devised to extend the traditional information retrieval approaches based on keyword search, with integrated capabilities of graph search, semantic search, fuzzy search and automated reasoning to realise the intelligent discovery of manufacturing resources, e. g. to facilitate more flexible, meaningful, accurate and automated resource discovery. A case study for intelligent discovery of manufacturing resources is used to demonstrate the practicality of the developed system.

  • CN
  • Zhejiang_Univ_ZJU (CN)
  • Zhejiang_Univ_Finance_&_Econ (CN)
Data keywords
  • ontology
  • semantic
  • knowledge
  • reasoning
  • knowledge retrieval
Agriculture keywords
  • supply chain
Data topic
  • information systems
  • semantics
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)
Powered by Lodex 8.20.3
logo commission europeenne
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.