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
To present and test an ecological multidimensional model of neighborhood characteristics and examine its relationship to older disability among older adults. Indicators of social vulnerability, wealth, violence, storefronts, residential stability, and the presence of physicians, supermarkets, and fast-food establishments for 1,644 of New Jersey's census tracts were derived from sources that include the U.S. Census 2000, Uniform Crime Report for New Jersey, New Jersey Department of Agriculture, Division of Marketing and Development, New Jersey Department of Law and Public Safety Division of Alcohol Beverage Control, and Health Resources and Services Administration Geospatial Data Warehouse. Confirmatory factor analyses were used to develop and test a measurement model of neighborhood texture. Structural equation modeling examined the relationships between neighborhood characteristics and disability of persons aged 65-69 years. Analyses revealed that distinct dimensions of neighborhoods could be modeled with administrative data and that neighborhood contextual (supermarkets, physicians, storefronts, violence) and compositional (social vulnerability, wealth, residential stability) characteristics were related to the prevalence of disability. The use of multiple indicators of neighborhood with good psychometric qualities is critical for advancing knowledge about the mechanisms by which neighborhood characteristics are associated with the health of older people.
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