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
One of the major source of information is database which plays an important role in computer field. Almost all IT applications are storing and retrieving information from databases. There are various interfaces available to retrieve data such as form based, natural language and keyword based. Data retrieval from the database requires knowledge of database language like SQL [1]. The need of natural language arises from the fact that common people (other than SQL experts) are not used to writing SQL query. Therefore researchers have identified a new system called Natural Language Interface to Database (NLIDB) and Keyword Based Interface to Database (KBIDB). In this paper we have proposed architecture of a Natural Language and Keyword Based Interface for Database (NLKBIDB) which provides solution for syntactically correct and incorrect natural language input query. Our partial experiment of Lexical Analyzer and Keyword based interface on agriculture survey database solves 53% of syntactically incorrect query which will not be solved by natural language interface resulting in increase of rate of SQL query conversion.
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