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
This paper discusses the knowledge acquisition problems faced in the Supply Chain Management (SCM) when acquiring knowledge among Supply Chain (SC) members, and it subsequently shows how modelling of knowledge types can be used as knowledge base to assist in solving SCM problems. This paper justifies the types of knowledge are useful in order to build knowledge bases to help decision makers and more importantly to help making decisions at the right time. The aim of this research is to explore knowledge types in the supply chain of food manufacturing firms. Our research method emphasizes content analysis and case study based on food manufacturing firm. As a result, we developed a model for the knowledge flow in SCM that advocates the knowledge that are relevant among SCM members. This model can dramatically save knowledge and, more fundamentally, allows for the knowledge engineers to build a knowledge based system based on this model. (C) 2013 The Authors. Published by Elsevier Ltd.
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