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
AutoIlD technology has been extensively used for a diversity of applications ranging from access control systems to airport baggage handling, livestock management systems, automated toll collection, theft-prevention, and automated production systems. Being able to efficiently perform complex real-time analysis on top of streams of RF10D events is a key challenge. This will provide management with a novel data analysis mechanism to allow better, tactical, on time, wellinformed decision-making. Challenges involve both syntactic and evaluation issues. In this paper we propose a set of linguistic requirements for MID data management (RFDM) queries and describe an SQL-like construct to address these. We argue that a large and useful class of (potentially complex) RFDM queries can be easily expressed and efficiently evaluated using this formality: start from a relational expression and successively extend it with columns representing aggregates over dynamically updated ordered sets. This incremental construction of a query is similar to formula definitions in spreadsheets. We present a fully functional prototype called COSTES (COntinuous SpreadsheeTlikE computationS) implementing spreadsheet-like queries and discuss its architecture and performance. We describe our system in the context of a supply chain management application.
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