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
Purpose: Innovation in agrifood supply chains requires transparency of information and knowledge. The objective of food informatics is to create web-based methods and tools to support continuous interaction between science, industry and society. Methodology/approach: A central theme is to apply technologies that express the semantics of research information. Due to the development of knowledge models (ontologies), computer systems become aware of food domain knowledge. The most important step in the context is to introduce a formal version of the most elementary natural language sentence (subject-predicate-object) and to refer to its parts using world-wide unique identifiers. This has been supplemented with logical constructs to allow complex reasoning. Findings: We have developed the ROC method: Rapid and Reuse-based Ontology Construction. This method makes knowledge modelling more efficient. ROC allows the domain expert to autonomously identify terms and concepts. The expert is supported in associative thinking. Secondly, we have developed a vocabulary to describe the core concepts and processes in quantitative (agrifood) research. We have implemented and evaluated this vocabulary in new tools to assist researchers. Practical implications: If more people understand the assumptions and mechanisms on which scientific results in agrifood are based, they have a better understanding of which actions to take. For food industry this means increased quality, sustainability and cost effectiveness in the industrial production process. The research management system Tiffany has been developed and implemented at TI Food and Nutrition. Secondly, ERDS, the emerging risks detection system scans signals on the web that point to events that eventually may cause food safety risks. A third application is Gateway2Food. This tool discloses knowledge in the field of food technology to small and medium size companies by allowing them to interactively search for experts.
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