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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A Grid-enabled problem-solving environment for advanced reservoir uncertainty analysis


Uncertainty analysis is critical for conducting reservoir performance prediction. However, it is challenging because it relies on (1) massive modeling-related. geographically distributed, terabyte, or even petabyte scale data sets (geoscience and engineering data), (2) needs to rapidly perforin hundreds or thousands of flow simulations, being identical runs with different models calculating the impacts of various uncertainty factors, (3) an integrated, secure, and easy-to-use problem-solving toolkit to assist uncertainty analysis. We leverage Grid computing technologies to address these challenges. We design and implement in integrated problem-solving environment ResGrid to effectively improve reservoir uncertainty analysis. The ResGrid consists of data management, execution management, and a Grid portal. Data Grid tools, such as metadata, replica, and transfer services', are used to meet massive size and geographically distributed characteristics of data sets. Workflow, task farming, and resource allocation are used to support large-scale computation. A Grid portal integrates the data management and the computation solution into a unified easy-to-use interface, enabling reservoir engineers to specify uncertainty factors of interest and perform large-scale reservoir studies through a web browser. The ResGrid has been used in petroleum engineering. Copyright (C) 2008 John Wiley & Sons, Ltd.

  • US
  • Louisiana_State_Univ_Baton_Rouge (US)
Data keywords
  • data management
Agriculture keywords
  • farming
Data topic
  • big data
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.