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
Reference process modelling in demand-driven agri-food supply chains: a configuration-based framework
Purpose: Agri-food companies increasingly participate in demand-driven supply chains that are able to adapt flexibly to changes in the marketplace. The objective of this chapter is to design a configuration-based framework for reference process modelling, which enhances the interoperability and agility of information systems as required in such dynamic supply chains. Methodology/approach: The research has designed a generic framework based on literature review and on an investigation of existing reference models. Next, the framework is tested in several agri-food sectors using a multiple case study approach. The case study results are abstracted to reusable models and incorporated in the framework. Findings: The main results are: a definition of basic design requirements for reference process models in demand-driven agri-food supply chains, an analysis of the extent to what existing reference models meet these requirements, a modeling framework for designing reference process models, and applications of the framework in agri-food industry. (Practical/managerial) implications: The designed framework supplies agri-food managers with a toolkit to model a broad variety of process configurations as apparent in agri-food supply chains. The framework comprises a consistent set of supply chain models, which intermediates between supply chain design and information systems engineering. As such it enhances shared understanding and reuse of both cross-industry and sector-specific process knowledge. However, successful adoption and industry-wide application of the designed framework requires an open innovation approach in further development and maintenance. Policy makers could play an important role in lowering the barriers for such an approach, since the additional benefits are not always obvious for individual companies, especially in the short term.
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