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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Farm machinery management information system


Management of farming operations is currently rapidly changing toward a systems perspective integrating the surroundings in terms of environmental impact, public entities and documentation of quality and growing conditions. The latest developments in Information and Communication Technologies (ICT) and the prevailing lack of interoperability between agricultural tractors, implements and on-board computers has led to the development of ISO 11783 (ISOBUS) international standard for securing a more effective communication between these entities. Precision agriculture requires an increasing amount of information in order to be sufficiently managed and the abilities of the ISOBUS protocol is a significant step toward this goal as it will provide a wealth of automated data acquisition for improving the management of crop production. However, there is an urgent need to organize and specify the pathways of this large amount of information as prerequisites for subsequently turning it into knowledge and decision_support. The aim of this study was to analyze and design a future farm machinery management information system to handle tractor and implement data together with the interactions with their surroundings. Soft systems methodology was used to analyze the human activities and to identify user requirements in relation to the use of farm machinery and the management of the information generated and pertaining to the tractor and the farm implements. The empirical data to extract this information was gathered from 30 targeted interviews with tractor operators and farm managers located in Greece and Denmark, and pertaining to questions about the optimal use of farm machinery data and tractor-implement performance. A rich picture of the whole system was developed and from that a conceptual model that infers to daily operations with the tractor, implement and the interactions with the surroundings. The conceptual models were developed for both conventional farm machinery and agricultural robots. The conceptual model function will serve as a blueprint for further development of required sensors, communication technology, and information processing capabilities. The developed conceptual models were tested and validated with 15 farm managers from the initial reviewing panel in order to reveal supplemental additions and concerns. (C) 2014 Elsevier B.V. All rights reserved.

  • GR
  • DK
  • Agr_Univ_Athens_AUA (GR)
  • Aarhus_Univ (DK)
  • Univ_Thessaly (GR)
Data keywords
  • information system
  • knowledge
Agriculture keywords
  • agriculture
  • farm
  • farming
Data topic
  • information systems
  • decision support
  • sensors
Document type

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

Institutions 10 co-publis
  • Agr_Univ_Athens_AUA (GR)
  • Aarhus_Univ (DK)
  • Univ_Thessaly (GR)
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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.