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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Semantically based reclassification of Danish land-use and land-cover information


In recent years, the availability of georeferenced data has increased substantially, as have the number of producers and users of this information. As a consequence, there is a growing need for harmonization of data, not least in its classification descriptions. Unfortunately, inadequate metadata hampers understanding of how data sets are produced and what data classes represent. This study describes how five different categorical geodata sets for Denmark, ranging from habitat registrations through maps of agricultural land use to national topographic data, are integrated and how the integrated data set is reclassified to land-use and land-cover classes. All five data sets differ with respect to data acquisition, and description and classification methodologies, and none of the data distinguish between land use and land cover. The purpose of the reclassification was to produce maps of land use and land cover, with classes being compatible with the land cover classification system (LCCS) from the Food and Agriculture Organization of the United Nations. We identified land-cover and land-use classes from the LCCS that matched Danish conditions and cross-tabulated those classes with classes from the integrated Danish data set. Based on the semantic meaning of the class names from the integrated data set, we used heuristic associational knowledge to estimate their membership in the land-use and land-cover classes. The results are three land-use maps and five land-cover maps, indicating qualitative estimates of the presence of land-cover classes measured on an ordinal scale.

  • DK
  • Univ_Copenhagen (DK)
  • Aarhus_Univ (DK)
Data keywords
  • data harmonization
  • knowledge
  • semantic
Agriculture keywords
  • agriculture
Data topic
  • modeling
Document type

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

Institutions 10 co-publis
  • Univ_Copenhagen (DK)
  • Aarhus_Univ (DK)
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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.