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
The environmental modelling community has developed many models with varying levels of complexity and functionality. Many of these have overlapping problem domains, have very similar 'science' and yet are not compatible with each other. The modelling community recognises the benefits to model exchange and reuse, but often it is perceived to be easier to (re)create a new model than to take an existing one and adapt it to new needs. Many of these third party models have been incorporated into the Agricultural Production Systems Simulator (APSIM), a farming systems modelling framework. Some of the issues encountered during this process were system boundary issues (the functional boundary between models and sub-models), mixed programming languages, differences in data semantics, intellectual property and ownership. This paper looks at these difficulties and how they were overcome. It explores some software development techniques that facilitated the process and discusses some guidelines that can not only make this process simpler but also move models towards framework independence. Crown Copyright (C) 2008 Published by Elsevier Ltd. All rights reserved.
Inappropriate format for Document type, expected simple value but got array, please use list format