The analysis of the cases shows that in practice all allowed a
number of actors from both domains (science and policy) to
participate in indicator development. However, science and policyled
processes had a different bias: in science-led processes there
was, by design, a bias towards the knowledge production
dimension, and less explicit recognition and inclusion of the
normative political dimension in the indicator development
process, particularly also with regard to participation, and thus
representation issues. This is partly due to the research project
character of these processes, which limits possibilities for
Table 8
Cases: selecting and adjusting indicators to changing social and political norms.
SI set (6) Selecting and adjusting sustainability indicators to
social and political norms
EFORWOOD Initial selection based on political selection process of EU SDI
and EU Sustainability Impact Assessment Guidelines,
no adjustment within the lifetime of the 4-year project
SENSOR Initial selection based on EU Sustainability Impact Assessment
Guidelines, but a few indicators representing new issues,
deemed relevant for multifunctional land use,
were added and developed
SEAMLESS The developed tool is generic to allow for adjustment,
but no adjustment was planned within the lifetime
of the project
MCPFE C&I Yes, in the first revision a few indicators were added
and others strengthened to better reflect emerging
political norms
EUROSTAT SDI Initial selection based on political (EU) strategy (mainly
the EU Sustainable Development Strategy). The SDI
set was adjusted to better reflect the revised EU SDS
68 E. Rametsteiner et al. / Ecological Indicators 11 (2011) 61–70
allocating large budgets and time for such purposes. Anecdotal
evidence also suggests that science-led processes (supposedly
focusing more on knowledge creation than social or political norm
building) find it more difficult to involve policy-makers in the
development process than vice versa, and there are questions of
how to get such indicator sets fully accepted and acknowledged as
legitimate by policy-makers. Certain aspects such as e.g. the spatial
scale (e.g. choice of NUTS3 region) may not be really chosen by
scientists, but may be a predetermined and thus influences the
development of the sustainability indicator set in a very specific
way. This raises the question: what is better, a slightly more
accurate but politically less relevant set, or a slightly less accurate
but politically more relevant set? And, from that follows: what is
the appropriate role of scientists in designing indicator sets:
moderators, knowledge brokers, or leaders of development
processes?