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
Subject Classification with DITA Markup for Agricultural Learning Resources: A Case Example in Agroforestry
Technical documentation and training materials are important elements in helping to accelerate the use and impact of agricultural research for development. The creation and delivery of these resources can be enhanced through content enrichment and the production and reuse of modular components. This process can be further improved by integrating rich semantic descriptions with resource metadata and domain-specific markup combined with the consistent use of controlled vocabulary. The Darwin Information Typing Architecture (DITA) supports both the integration of metadata as well as markup for technical as well as learning and training content. DITA also includes mechanisms for adding the semantics of taxonomy and ontology definitions for classifying content. This paper explores the potential use Of enriching agroforestry learning resources with DITA markup through descriptive metadata and subject classification.
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