e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

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.

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Developing a biocuration workflow for AgBase, a non- model organism database


AgBase provides annotation for agricultural gene products using the Gene Ontology (GO) and Plant Ontology, as appropriate. Unlike model organism species, agricultural species have a body of literature that does not just focus on gene function; to improve efficiency, we use text mining to identify literature for curation. The first component of our annotation interface is the gene prioritization interface that ranks gene products for annotation. Biocurators select the top-ranked gene and mark annotation for these genes as 'in progress' or 'completed'; links enable biocurators to move directly to our biocuration interface (BI). Our BI includes all current GO annotation for gene products and is the main interface to add/modify AgBase curation data. The BI also displays Extracting Genic Information from Text (eGIFT) results for each gene product. eGIFT is a web-based, text-mining tool that associates ranked, informative terms (iTerms) and the articles and sentences containing them, with genes. Moreover, iTerms are linked to GO terms, where they match either a GO term name or a synonym. This enables AgBase biocurators to rapidly identify literature for further curation based on possible GO terms. Because most agricultural species do not have standardized literature, eGIFT searches all gene names and synonyms to associate articles with genes. As many of the gene names can be ambiguous, eGIFT applies a disambiguation step to remove matches that do not correspond to this gene, and filtering is applied to remove abstracts that mention a gene in passing. The BI is linked to our Journal Database (JDB) where corresponding journal citations are stored. Just as importantly, biocurators also add to the JDB citations that have no GO annotation. The AgBase BI also supports bulk annotation upload to facilitate our Inferred from electronic annotation of agricultural gene products. All annotations must pass standard GO Consortium quality checking before release in AgBase. Database URL: http://www.agbase.msstate.edu/

  • US
  • Mississippi_State_Univ (US)
  • Univ_Delaware (US)
Data keywords
  • ontology
Agriculture keywords
  • agriculture
Data topic
  • information systems
  • modeling
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • Mississippi_State_Univ (US)
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e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.