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
For decision makers in the domains of agriculture and environment, for instance in government agencies, farming, and environmental NGOs it is beneficial to evaluate ex-post or to asses ex-ante the impacts of their choices. Modelling and modelling tools can be helpful by providing a simplified representation of reality, simulating potential contrasting pathways into the future and improving the understanding of interdisciplinary cause-and-effect relationships. To research these interdisciplinary relationships, models developed by different scientific disciplines and often operating at different scales can be integrated into model chains that cover processes across disciplines. Integration allows the single disciplinary models to complement each other and thereby provide comprehensive and balanced assessments across scales and disciplines. In order to assemble models into an operational model chain multiple levels of integration have to be taken into account. First and foremost methodological or conceptual integration has to take place, which focuses on aligning different scientific methodologies and identifying required model improvements necessary for meaningful linkage. Secondly semantic integration has to take place to achieve the use of a common language to describe the models and the data they consume and produce in order to avoid failed integration due to ambiguous or misunderstood terminology. It also helps in reaching shared understanding and goals between the modellers involved. Thirdly, and the main focus of this paper, technical integration has to take place. Here the aim is to ensure repeatability and reproducibility of model chain runs and to optimize use of computer hardware for model simulations. Technical integration itself can be achieved by different approaches (i.e. manual, scripting, building or using a proprietary framework, using an open framework based on standards). The choice of approach depends on the institutional and project context and on the preferences of the researchers involved. This paper will further focus on framework based technical integration. From the many available modelling frameworks (e. g. OMS, TIME, KEPLER, FRAMES, MODCOM, OpenMI, etc.) the emphasis will be on OpenMI, the Open Modelling Interface and its use and usefulness as a readily available, generally accepted and open standards based framework. OpenMI is a open source software standard for dynamically linking models at runtime, which can potentially be used in many domains, but is currently mainly applied in the water and environmental domains. This paper examines the use of OpenMI in several multi-disciplinary large projects that worked on integrated models. These projects operated in the disciplines of agriculture, land use, nitrogen cycling, forestry, hydrology and economics. The overall objective is to investigate the strengths and weaknesses of integrated modelling according to open frameworks based on standards in general, and OpenMI in particular, based on feedback from both software developers and modellers that contributed to the aforementioned projects on the use of OpenMI, combined with the authors' knowledge and experience. Recommendations for improvements of OpenMI specific and integrated modelling in general will be presented. Preliminary findings point to the existence of tension between building a model with a stand-alone purpose and building a model suitable to be linked to other models. Making a model linkable turns out to be an effort that is neither a primary goal for the modeler or for the framework developer. This is not helped by the typical OpenMI framework Software Development Kit (SDK) implementation tending to have a fairly heavy weight impact on the models, where recent studies promote a more lightweight approach to frameworks to make their adoption easier. Steps taken at Alterra in the development of the OpenMI 2.0 SDK for Java to improve this situation will also be mentioned.
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