Focus 2: Conceptual and mathematical models to integrate fragmented data from lab and field studies
While the above-mentioned problems are inherently complex, information needed to derive solutions is scattered. Data are collected by various disciplines, in laboratory experiments and field surveys, carried out at different conditions, measuring different physical-chemical pressures and biological responses. To allow diagnosis and prognosis, coherent frameworks are indispensible. We therefore focus on the development and application of conceptual and mathematical models and databases that allow:
- scattered information to become consistent knowledge
- qualitative judgements to be replaced by quantitative assessments
- causes to be linked mechanistically to consequences
- understanding to be followed by predicting
The models are in between an exact and an abstract description of reality. They should be sufficiently abstract to allow application to many cases and at the same time allow calibration and validation with data. The data needed are often collected in collaboration with other departments and organizations. In research, it allows modelling, laboratory and field experts to help each other. In education, students get the opportunity to link their own case studies to issues that they will have to deal with in their working life later. Examples of these models include BIOSAFE, USES-LCA and OMEGA.