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
This paper introduces CODA (Computer-aided Ontology Development Architecture), which is both an architecture and an associated framework supporting the transformation of unstructured and semi-structured content into RDF (Resource Description Framework) datasets. The purpose of CODA is to support the entire process that ranges from data extraction and transformation to identity resolution. The final objective is to feed semantic repositories with knowledge extracted from unstructured content. The motivation behind CODA lies in the large effort and design issues required for developing knowledge acquisition systems using content analytics frameworks such as UIMA (TM) (Unstructured Information Management Architecture) and GATE (General Architecture for Text Engineering). Therefore, CODA extends UIMA with facilities and a powerful language for projection and transformation of UIMA-annotated content into RDF. The proposed platform is oriented towards a wide range of beneficiaries, from semantic applications developers to final users that can easily plug CODA components into compliant desktop tools. We describe and discuss the features of CODA through the article, and we conclude by reporting on the adoption of the CODA framework in the context of a usage scenario, related to knowledge acquisition in the agricultural domain.
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