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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Data integration technologies to support integrated modelling


Over the recent years the scientific activities of our organisation in large research projects show a shifting priority from model integration to the integration of data itself. Our work in several large projects on integrated modelling for impact assessment studies has clearly shown the importance of data availability for integrated modelling, but of no less importance is the integration, or alignment, of the required input data itself. Moving from the fairly technical model integration in OpenMI and OpenMI related projects, and moving towards basic semantic integration in the SEAMLESS and SENSOR projects, our focus is now shifting towards researching and applying techniques such as Semantic Web technologies to improve data discoverability, its integration, and in the future on reasoning about the constructed integrated knowledge. This paper will present an overview of the on-going work in our European 7th Framework Programme (FP7) project TREES4FUTURE, focussing on automated harvesting of forestry related data sets and enriching its meta data for search ability; the FP7 LIAISE Network of Excellence on linking impact assessment instruments such as models and data to sustainability expertise; and the FP7 research project SEMAGROW on developing visions on processing and querying large RDF triple-stores of integrated agricultural data. In the end we aim at bringing the results of all these projects together to achieve a next step in integrated modelling and to present ways to use Natural Language Processing based methods to help providing meta data.

  • NL
  • Wageningen_Univ_and_Res_Ctr_WUR (NL)
Data keywords
  • semantic
  • natural language processing
  • knowledge
  • rdf
  • reasoning
Agriculture keywords
  • agriculture
Data topic
  • big data
  • information systems
  • modeling
  • semantics
Document type

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

Institutions 10 co-publis
  • Wageningen_Univ_and_Res_Ctr_WUR (NL)
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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.