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
The size of agricultural databases continues to increase, and sources of information are growing more and more diversified. This is especially the case for databases dedicated to the traceability of agricultural practices. Some data are directly collected from the field using embedded devices; other data are entered by means of different computer-based applications. Once stored in the same database, all this information must be consistent to guarantee the quality of the data. This consistency issue is becoming a new challenge for agricultural databases, especially when complex data are stored (for instance, georeferenced information). To achieve consistency in a database, a precise, formal specification of the integrity constraints is needed. Indeed, database designers and administrators need a language that facilitates the conceptual modeling of this type of constraint. In this chapter, we introduce the Object Constraint Language (OCL), using the example of an agricultural database for organic waste management. The example of a tool supporting OCL (the Dresden OCL Toolkit) and an overview of a spatial extension of the language will be also presented.
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