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.

You can access and play with the graphs:

Discover all records
Home page


Trade-offs in the design of cross-disciplinary software systems


As researchers we are often faced with the difficult and demanding task of preparing models, and their computer implementations, for decision making, or, more recently, for integrated assessment. Such assessment often involves large scale problems, where the decisions to be made can deeply affect the environment, the social context and the economic background of regions and even nations. Yet, we face the grim reality that a model is a focused representation of the world, and it is always a result of several compromises in terms of details and structure, leading to trade-offs in terms of complexity, flexibility and performance. This trade-off becomes an essential design property. We often wish our models to be as simple as possible, balancing transparency, understandability and level of detail. Now, we are involved in the SEAMLESS project, an EU FP6 Integrated Project, aims at generating an integrated framework of computer models. This framework can be used for assessment of how future alternative agricultural and environmental polices affect sustainable development in Europe. Thus, we are designing a cross disciplinary software system to deal with different simulation domains. In this, we need to take care of many differences between the different modeling societies. We decided to apply an architecture centric development method and evaluated this with stakeholders based on a so-called Architecture Trade-off Analysis method. When prioritizing the requirements we used a cost-benefit analysis as a weighting factor for deciding what to do first. Requirements were grouped in user-roles, that appeal to differences in user-interface options. The resulting software architecture identified the necessity to identify two major blocks: the modeling environment, to be used by a number of user roles, mostly modelers and coders, and the processing environment, which is oriented towards the needs of those user roles more focused on system analysis, rather than design and implementation. Another key factor of our architecture is the knowledge base, which provides a common repository for all knowledge, data, model sources which are shared by the two environments. When moving on from architecture to design and implementation, we tried to steer clear of the risk of inventing another modelling framework, and therefore in our prototype we use different existing frameworks for different tasks in the overall design. This means that we discussed the view that 'one tool fixes everything', and we chose to rely on specific frameworks for specific needs. We chose a modelling framework with a track record in crop modeling, to target our biophysical modeling needs, and we selected a de facto standard framework for economic modeling to solve agri-economic modelling problems. All of this comes at a price, that is the extra effort required to integrate different frameworks. We chose therefore to develop an evolution of the OpenMI integration framework to target this issue. In this article we describe all the risks we have identified as associated to our architecture centric approach and how we dealt with them. This article describes the design of the modeling framework for SEAMLESS. A first prototype is ready in January 2006.

      Data keywords
      • ontology
      • knowledge
      • knowledge based
      Agriculture keywords
      • agriculture
      Data topic
      • information systems
      • modeling
      • semantics
      Document type

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

      Institutions 10 co-publis
        Powered by Lodex 8.20.3
        logo commission europeenne
        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.