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Internet and the use of data for
International Affairs | | |
Characteristics
So far we have introduced and described the concept of indicator but what are the properties a good
indicator should have? What
are the principles to tell a good indicator from a bad one?
IISD
has selected criteria to help create a minimum level of
comparability, coherence and consistency between measures and their application to real-life situations.
Policy relevance
Can the indicator be associated with one or several issues around which key policies are formulated?
Usually indicators are
intended for audiences to improve the outcome of decision-making on levels ranging from individuals
to the entire biosphere.
Unless the indicator can be linked by readers to critical decisions and policies, it is unlikely to
motivate action.
Simplicity
Can the information be presented in an easily understandable, appealing way to the target audience?
Even complex issues and
calculations should eventually yield clearly presentable information that the public understands.
Validity
Is the indicator a true reflection of the facts? Was the data collected using scientifically defensible
measurement techniques? Is
the indicator verifiable and reproducible? Methodological rigor is needed to make the data credible
for both experts and laypeople.
Time-series data
Is time-series data available, reflecting the trend of the indicator over time? If based on only
one or two data points, it is not
possible to visualize the direction the community may be going in the near future.
Availability of affordable data
Is good quality data available at a reasonable cost or is it feasible to initiate a monitoring process
that will make it available in the
future? Information tends to cost money, or at least time and effort from many volunteers.
Ability to aggregate information
Is the indicator about a very narrow or broader issue? The list of potential indicators is on a
specific issue is sometime endless.
For practical reasons, indicators that aggregate information on broader issues should be preferred.
Another key aspect is that
indices simplify complex systems to often just one number. This is useful for decision-makers but if
importaant pieces of
information are missing or improperly represented in an index, that can give a false signal to them.
Sensitivity
Can the indicator detect a small change in the system? We need to determine beforehand if small
or large changes are relevant
for monitoring.
Reliability
Will you arrive at the same result if you make two or more measurements of the same indicator? Would
two different researchers
arrive at the same conclusions?
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