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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Genome Analysis of Species of Agricultural Interest


In recent years, the role of bioinformatics in supporting structural and functional genomics and the analysis of the molecules that are expressed in a cell has become fundamental for data management, interpretation, and modeling. This interdisciplinary research area provides methods that aim not only to detect and to extract information from a massive quantity of data but also to predict the structure and function of biomolecules and to model biological systems of small and medium complexity. Although bioinformatics provides a major support for experimental practice, it mainly plays a complementary role in scientific research. Indeed, bioinformatics methods are typically appropriate for large-scale analyses and cannot be replaced with experimental approaches. Specialized databases, semiautomated analyses, and data mining methods are powerful tools in performing large-scale analyses aiming to (1) obtain comprehensive collections; (ii) manage, classify, and explore the data as a whole; and (iii) derive novel features, properties, and relationships. Such methods are thus suitable for providing novel views and supporting in-depth understanding of biological system behavior and designing reliable models. The success of bioinformatics approaches is directly dependent on the efficiency of data integration and on the value-added information that it produces. This is, in turn, determined by the diversity of data sources and by the quality of the annotation they are endowed with. To fulfill these requirements, we designed the computational platform ISOLA, in the framework of the International Solanaceae Genomics Project. ISOLA is an Italian genomics resource dedicated to the Solanaceae family and was conceived to collect data produced by 'omics' technologies. Its main features and tools are presented and discussed as an example of how to convert experimental data into biological information that in turn is the basis for modeling biological systems.

  • IT
  • Univ_Napoli_Federico_II (IT)
Data keywords
  • data management
Agriculture keywords
  • agriculture
Data topic
  • big data
Document type

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

Institutions 10 co-publis
  • Univ_Napoli_Federico_II (IT)
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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.