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
Fish disease diagnosis is a complicated process and requires high level of expertise. However, there's no accepted general knowledge in fish disease diagnosis. This paper describes a web-based CBR (case-based reasoning) system for fish disease diagnosis. Instead of relying on general domain knowledge, CBR utilizes the specific knowledge of previous cases and solves a new problem by hunting out a similar case, and reusing it in the new problem. A two-step case retrieve model is proposed in this paper. The new case is initially identified which case base it belongs to, then the similarity is calculated using nearest neighbor method between the new case and the previous cases in the case base, finally the most similar one is found out and the solution is reused. The process of developing the web-based CBR system for fish disease diagnosis, the system structure and its components, such as knowledge base, case base and their functions, are described in this paper. Some experiences with developing CBR system are discussed and conclusions are provided at the end of the paper.
Inappropriate format for Document type, expected simple value but got array, please use list format