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
An Analysis and Design of Frozen Shrimp Traceability System Based on Digital Business Ecosystem
Traceability system is one of the most critical requirements in logistic information systems and the supply chain risk management for both global food safety and quality assurance. Realtime documentation from the earlier stages of production process enabled the two way process of traceability. This paper presented an analysis and design for traceability system of frozen Vanname shrimp based on digital business ecosystems ( DBE) model. Business Process Model Notation ( BPMN 2.0) was the primary tool in analyzing the task for capturing and transferring data processing between traceable units in each layer of DBE. Business process analysis helped to understand the capturing steps as the main element within such traceability system. The results of the analysis showcased how traceability system work in digital business ecosystem which involved on dispersed stakeholders. Manual data transformation to the digital system was provided by stakeholders using digital species metaphors. The requirement for factor analysis was computed with Relief method to select the most important attribute to capture. Our evaluation showed that the proposed system was able for estimating water salinity and related hatchery parameters changing, such as broodstock ID which utilized as key code. Current results showed the readiness of application to transfer into real world operation.
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