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
For the last 20 years, developmental psychologists have measured the variability in lexical development of infants and toddlers\ using the MacArthur-Bates Communicative Development Inventories (CDIs) - the most widely used parental report farms/or assessing language and communication skills in infants and toddlers. We show that CDI reports can serve as a basis for estimating infants' and toddlers' total vocabulary sizes, beyond serving as a tool for assessing their language development relative to other infants and toddlers. We investigate the link between estimated total vocabulary size and raw CDI scores from a mathematical perspective, using both single developmental trajectories and population data. The method capitalizes on robust regularities, such as the overlap of individual vocabularies observed across infants and toddlers, and takes into account both shared knowledge and idiosyncratic knowledge. This statistical approach enables researchers to approximate the total vocabulary size of an Want or a toddler based on her raw MacArthur-Bates CDI score. Using the model, we propose new normative data for productive and receptive vocabulary in early childhood, as well as a tabulation that relates individual CDI measures to realistic lexical estimates. The correction required to estimate total vocabulary is non-lineal; with a far greater impact at older ages and higher CDI scores. Therefore, we suggest that correlations of developmental indices to language skills should be made to vocabulary size as estimated by the model rather than to raw CDI scores.
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