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
A methodology to allow rural extension professionals to build target-specific expert systems for Australian rural business operators
Expert systems (ES) development technology has been used to build rural business applications in the past but these have usually been developed using traditional expert systems shells. This paper introduces a new architecture for the development of a design environment where the domain experts can build a knowledge base for target-specific ES for rural business operators. The system allows rural business operators to use their own knowledge in building their own, target-specific ES for tailored development to their own specific requirements. At this stage, this reusable design environment caters for the Australian dairy industry but in the long run we claim it will be useful for the other livestock based rural industries such as beef cattle and sheep. This approach of developing target-specific ES contributes new knowledge in that it provides a new way of developing decision_support by allowing human domain experts to develop relevant ES for different livestock farming business. An evolutionary prototyping approach was employed for initial development of a proof of concept example and as a method of outlining the solution environment. Multiple qualitative data collection methods were engaged to facilitate knowledge acquisition in the domain of milk protein enhancement for dairy operations. This paper also describes the generic development procedure used in this project. (C) 2007 Elsevier Ltd. All rights reserved.
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