Gedetailleerde leidraad

A.1 Uncertainty location

This dimension indicates where uncertainty can manifest itself in the problem configuration at hand. Five categories are distinguished along this dimension:

  • The 'context' concerns the framing of the problem, including the choices determining what is considered inside and outside the system boundaries ('delineation of the system and its environment'), as well as the completeness of this representation in view of the problem issues at hand. Part of these context-related choices is also reflected in the other location categories, such as 'data' which are considered to play a role, 'models' which are chosen to be used, and 'outcomes' which are taken to be of interest.
  • 'Data' refers to e.g. measurements, monitoring data, survey data etc. used in the study, that is the category of information which is directly based on empirical research and data gathering. Also the data which are used for calibration of the models involved are included in this category.
  • 'Model' [3] concerns the 'model instruments' which are employed for the study. This category can encompass a broad spectrum of models, ranging from mental and conceptual models to more mathematical models (statistical models, causal process models etc.) which are often implemented as computer models. Especially for the latter class of models subcategories have been introduced, distinguishing between model structure (relations), model parameters (process parameters, initial and boundary conditions), model inputs (input data, external driving forces), as well as the technical model, which refers to the implementation in hard and software.
  • 'Expert judgment' refers to those specific contributions to the assessment that are not fully covered by context, models and data, and that typically have a more qualitative, reflective, and interpretative character. As such this input could also be alternatively viewed as part of the 'mental model'.
  • The category 'Outputs' from a study refers to the outcomes, indicators, propositions or statements which are of interest in the context of the problem at hand.

Remark Notice that 'scenarios' in a broad sense have not been included as a separate category on the location axis. In fact they show up at different locations, e.g. as part of the context, model structure, model input scenario, expert judgment etc.

The various aforementioned uncertainties on the location axis can be further characterized in terms of four other uncertainty features/dimensions, which are described in the subsequent sections.

[3] We define 'models' in a broad sense: a model is a (material) representation of an idea, object, process or mental construct. A model can exist solely in the human mind (mental, conceptual model), or be a physical representation of a larger object (physical scale model), or be a more quantitative description, using mathematical concepts and computers (mathematical and computer model).