A.1 Uncertainty locationThis 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.
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