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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Use of Expert System and Data Analysis Technologies in Automation of Error Detection, Diagnosis and Recovery for ATLAS Trigger-DAQ Control Framework


Trigger and Data Acquisition (TDAQ) System of the ATLAS experiment on LHC at CERN is a very complex distributed computing system, composed of O(10000) applications running on a farm of commodity CPUs. The system is being designed and developed by dozens of software engineers and physicists since end of 1990's and it will be maintained in operational mode during the lifetime of the experiment. The TDAQ system is controlled by the Control framework, which includes a set of software components and tools used for system configuration, distributed processes handling, synchronization of Run Control state transitions etc. The huge flow of operational monitoring data produced is constantly monitored by operators and experts in order to detect problems or misbehavior. Given the scale of the system and the rates of data to be analyzed, the automation of the Control framework functionality in the areas of operational monitoring, system verification, error detection and recovery is a strong requirement. The paper describes requirements, technologies choice, high-level design and some implementation aspects of advanced Control tools based on knowledge-base technologies. The main aim of these tools is to store and to reuse developers expertise and operational knowledge in order to help TDAQ operators to control the system with maximum efficiency during life time of the experiment.

  • CH
  • RU
  • US
  • CERN_Org_Europ_Rech_Nucl (CH)
  • Univ_Calif_Irvine (US)
Data keywords
  • knowledge
  • knowledge based
  • distributed computing
Agriculture keywords
  • farm
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
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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.