SEAMLESS

SEAMLESS developed an integrated framework with computer models for ex-ante assessment of alternative agricultural and environmental policy options for sustainable development in Europe. The project has been set up in response to a research and policy need formulated by the European Commission. The SEAMLESS integrated and operational framework included quantitative models that simulate effects of the biophysical environment and economic developments, next to procedures that enable assessment of the qualitative aspects such as quality of life and visual landscape quality. The computer system facilitated the integration of models from a wide range of scientific domains.

I was involved on tasks related to software engineering for environmental model component integration tackling issues related with the complexity of environmental software and its implementations. This intrigued me to investigate Ontology-driven Software Engineering (ODISE) methods, including topics on the integration of heterogeneous environmental model components, the annotation of model interfaces using e-science ontologies, and the semantic-rich development architecture to manage domain knowledge lifecycle. For this work, we received the EURO SIWzie Best Paper Award of the Simulation Interoperability Standards Organization (SISO), in 2007.

Also, I co-lead the effort of the data and ontology task force (DOT Force), that researched how ontologies can be used for the seamless integration of agricultural data and models, and developed a set of ontologies in order to facilitate the integration of a variety of combinatorial, simulation and optimization models related to agriculture. The developed ontologies have been exploited in the software lifecycle, by using them to specify data communication across the models, and with a relational database. The Seamless ontologies provide with definitions for crops and crop products, agricultural feasibility filters, agricultural management, and economic valuation of crop products, and agricultural and environmental policy, which are in principle the main types of data exchanged by the models. Issues related to translating data structures between model programming languages have been successfully tackled by employing annotations in the ontology.

In the context of Seamless, I researched semantic modeling in environmental sciences, and focused on indirectly-driven knowledge modeling and upper ontologies for scientific observations, and emerging semantic approaches to environmental modeling. This work resulted in a long-term collaboration with the Ecoinformatics Lab at the University of Vermont, and the release of two open-source tools for semantic modeling (ThinkLab) and a knowledge portal (ThinkCap) that allows for extensive customization.