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
Streamlining life cycle inventory data generation in agriculture using traceability data and information and communication technologies - part I: concepts and technical basis
Quantitative environmental assessment methodologies such as life cycle assessment demand significant time and resource inputs during the data acquisition and life cycle inventory (LCI) phase. Approaches to streamline the LCI data collection process without degrading data quality are therefore required. This requirement is especially true for agricultural products, as agricultural systems are inherently 'open' and complex. We present a two-part paper on this topic. In this first part, we examine streamlined methods for LCI data collection in agriculture by using today's voluntary or compulsory farm traceability information systems and related information and communication technologies (ICTs), with the aim of later converting them into LCI data. The second part is to examine the application of these technologies in a case study. Our hypothesis is that both traceability data and ICTs could be major drivers for generating accurate, relevant and low-cost LCI data for use in quantitative environmental assessments of agricultural product performance. To that end, we identified the types of data being collected in agriculture as a part of current business practice, especially those with relevance to LCA studies. We also examined the status and current trends in ICTs in use in agriculture to identify the potential for automating LCI data generation. The review identified considerable potential to piggy-back current trends in ICTs in agriculture with the goal of simplifying LCI data collection. This study concludes that given the increasing need to collect traceability data in modern agriculture and the parallel growing adoption of information and communication technologies, it is likely that ICTs and associated information systems will represent an important potential route for the acquisition of future LCI data. (C) 2014 Elsevier Ltd. All rights reserved.
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