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


A Survey on the Application of Neural Networks In the Safety Assessment of Oil and Gas Pipelines


Pipeline systems are an essential component of the oil and gas supply chain today. Although considered among the safest transportation methods, pipelines are still prone to failure due to corrosion and other types of defects. Such failures can lead to serious accidents resulting in big losses to life and the environment. It is therefore crucial for pipeline operators to reliably detect pipeline defects in an accurate and timely manner. Because of the size and complexity of pipeline systems, however, relying on human operators to perform the inspection is not possible. Automating the inspection process has been an important goal for the pipeline industry for a number of years. Significant progress has been made in that regard, and available techniques combine analytical modeling, numerical computations, and machine learning. This paper presents a survey of state-of-the-art methods used to assess the safety of the oil and gas pipelines. The paper explains the principles behind each method, highlights the setting where each method is most effective, and shows how several methods can be combined to achieve a higher level of accuracy.

  • CA
  • QA
  • Concordia_Univ (CA)
Data keywords
  • machine learning
Agriculture keywords
  • supply chain
Data topic
  • information systems
  • sensors
Document type

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

Institutions 10 co-publis
    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.