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
As the use of information technology becomes more ubiquitous, the need for data processing and storage capabilities increases. This results in the construction and operation of large data centers-facilities that house thousands of servers and serve as the backbone for all types of computational processes. Unfortunately, as processing power and storage capacity increases, so does the corresponding power and cooling requirements of the data centers. Several studies have examined the efficiency of data centers by focusing on server and cooling power inputs, but this fails to capture the data center's entire impact. To accomplish this, the use of a lifetime exergy (available energy) analysis is proposed. This study first details the development of a lifetime exergy consumption model designed specifically for data center analysis. To create a database of computer components, a disassembly analysis was performed, and the results are detailed. By combining the disassembly analysis of a server with the aggregation of energy and material data, a more rigorous and useful assessment of the server's overall impact is demonstrated. The operation of the lifetime exergy consumption model is demonstrated by case studies examining the effects of variance in transportation and cooling strategies. The importance of transportation modes and material mass, which are greatly affected by supply chain parameters, is shown. The impact of static and dynamic cooling within data centers is also demonstrated.
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