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:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Recently there has been a great demand for extending high throughput life science research to bio-manufacturing. However, there is a gap from life science research to bio-manufacturing. Most existing bio-workflow tools/grid computing systems only provide an isolated solution to help bio-scientist to orchestrate bio-R&D operations such as bio-database query, bio-computation and analysis for biological problems in specific verticals. They are static and lack the ability to adapt in a dynamic changing environment. Manufacturing of biological materials such as diagnostics, therapeutics and prophylactics, or bio-manufacturing, typically involves many bioprocesses, each of which requires a set of bio-workflows to be choreographed. This is currently achieved by manually defining and managing the workflows for bioprocesses through different workflow tools. This paper proposes a novel goal-oriented approach to modeling bioprocesses, choreographing bio-workflows from different workflow tools, and to integrating agents, web services and workflows for automated execution. It demonstrates how a multi-agent system on a grid infrastructure can be further derived to adapt and automate complex bio-manufacturing workflow/processes in a dynamic changing environment. In this way, database access in a large data grids, high performance computing in a computational grid, and remote device control in a manufacturing grid, can be coupled to a supply chain management system to form a broad scale bio-manufacturing grid that streamlines the entire value chain from R&D, productisation and design of biological products.
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