Environmental Engineering Reference
In-Depth Information
The latter request can be met through the visualization techniques are elaborated in
the presentation part of the interface.
The reason for the two requests in the examples above can be traced directly
back to the everyday practical assessment work of the services. They are also easily
understood and translated by the researchers. Other requests could have their
background in more profound political dimensions of the IA work and were not so
easily transformed into the tool, like the questions of transparency and uncertainty
of results.
The participants repeatedly expressed their concern for lack of transparency of
modelling systems in general. The demand for transparency stems from a basic
need for policy making institutions that their work gains legitimacy. Legitimacy is
achieved when the production of knowledge, that a policy is based on, has been
conducted in an unbiased way and has treated opposing interests in a fair manner.
The modelling part of an assessment must not be suspected of taking over any
political agenda. In the practical work situation the issue of transparency means that
assessment leaders and other policy makers have to be able to defend and explain
modelling results to a critical group of stakeholders. If the modelling system is a black
box, where assumptions and other critical parameters are not clear and understandable
the outcome might not be perceived as useful (salient) for the officers in charge.
The demand for transparency is met with a comprehensive documentation of
each of the components and the entire framework. Also the development of a joint
ontology for concepts that are shared across components serves the aim of transparency
and consistency (Janssen et al.
2009)
. Further, the need for transparency has
triggered a large investment to develop graphical user interfaces for two user types,
to define and document the specifications of impact assessment experiments with
SEAMLESS-IF.
We also learned that the issue of uncertainty of results was important. The closer
the process gets to policy implementation the more important the aspect of
uncertainty becomes. Information about uncertainty must be based on what users
find important and the project therefore needed to get a deeper understanding of
this issue. This experience encouraged the project to adopt a user-oriented approach
towards uncertainty analysis (Gabbert et al.
2009)
. As part of this approach a
questionnaire with the aim to capture the most important aspects of uncertainty was
distributed to participants of the User Forum and other contacts at various DGs,
JRC and EEA. The questionnaire revealed which items of uncertainty potential users
find most relevant. Although answers from respondents differ, they do give some
guidance towards concrete uncertainty analyses in comprehensive model chains such
as SEAMLESS-IF. A full blown traditional and forward approach to uncertainty
analysis is neither feasible nor effective; instead a focus on relevant sources and
aspects of uncertainty as identified by users and scientists is opted for (ibid.).
The political character of an IA process was also transformed into requests like
the need for a very flexible selection of indicators. A situation where policy makers
would be completely free to suggest their own indicators would be the optimal
situation. The reason for this was that during the course of an IA, negotiations
between several DGs and stakeholders are needed. If the selection of indicators is
