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
Building a distributed agricultural inforiuation system (DAIS) is an important task to implement agriculture infort-natisation. Due to the limitations of network flux and the characters of spatial data, access to huge agricultural geospatial datasets often suffers from slow or unreliable network connections. This limits the development and application of WebGIS in agriculture. To improve the response speed for access to the agricultural geospatial data, this paper introduces a solution for vector data simplification based on the improved Douglas-Peucker algorithm and a binary line generalisation (BLG) tree. Accordingly, this paper discusses the techniques for progressive transmission of vector data, i.e., the architecture of WebGIS, data organising and coding on the server-side. The experimental results show that the method proposed in this paper can not only effectively reduce system response time, but also preserve the topology relation between spatial data, which sequentially improves the performance and quality of DAIS.
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