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Regional geographic information infrastructure in the Hindu Kush – Himalayan Region
Obviously, the development and the
maintenance of a spatial data infrastructure require institutions with qualified
staff. Three main issues have to be addressed in GIS education and training
programmes:
- chnical officers must become ‘agents of change’, and they must be provided
with the tools to be that; i.e. they must enjoy a certain liberty to develop and
test new technologies, and they must be allowed to express their views. To avoid
constant brain drain, they must also be remunerated according to market
salaries.
- Education has to be done concurrently at all levels of hierarchy within
organisations (technical, middle and high management)
- A critical mass of trained people (at least 10% of staff in any given
institution) is required to overcome inevitable losses of highly qualified
staff.
Moreover, the institutions also need to carefully re-think
their business process. Using computers to mimic conventional workflows and
management is normally not an efficient utilisation of the new technologies.
Policies
Coherent policies on a number of issues are a very
important component of a spatial data infrastructure. While each of these issues
can be solved in a variety of different ways with their own advantages and
disadvantages, the important fact for the user is that there exists a coherent
policy, on which he can base his investments. Policy issues are:
- Access to and use of the spatial data infrastructure Who can get access to
which spatial data? Where is the trade-off between the legitimate interests of
security, development, and business? What kinds of use are permissible? How
about privacy rights of the individual?
- Copyright and liability: Unfortunately, there are no simple technical means
to prevent the pirating of data. Moreover, under the prevailing laws on
copyright, which demand a certain originality of a product to make it subject to
copyright, it is often not clear whether spatial data which are a mere record of
facts, are protected. The status of derived and value-added products is even
less clear. Hence a clear copyright law that is specifically catering to digital
data is necessary.
On the other hand, the question of liability should be
addressed. Is the producer of a Digital Elevation Model responsible if a plane
crashes into a mountain because of an error in the model? Pricing and financing
Information is a special kind of commodity: its use is non exclusive, the
quantity is difficult to measure, and it has the character of a public good.
Further, it is questionable if all users should be charged the same price.
Therefore it is difficult to set a fair price, and the market doesn’t really
play. This issues boils down to the question whether the spatial data
infrastructure is considered a public utility that can be used by anybody
regardless of his financial means, or a profit centre which has to recover its
cost.
- Education and awareness building Building a database of primary GIS data is
a complex technical process which requires specialists. These are often detached
from the potential users and find it difficult to bring the data or the results
of their analysis into a format which is useful for the end users (e.g. policy
makers). On the other hand, potential users are often unaware of the information
and the analytical capacities that exist. Hence some efforts are required to
carry the message outside the community of the technical people who actually
deal with GIS and bridge the gap between producers and potential users of
geographical information.
- Research & Development A long-term perspective on applied research and
development should be in place to facilitate adopti9on of new technologies and
further development of applications and products.
- Institutional Coordination Last, but not least, a strong institutional
coordination is required. A spatial data infrastructure is a horizontal (i.e.
cross-sectrol ) structure, its creation and use requires a joint effort of the
various stakeholders. Contrarily, existing government machineries at all
administrative levels are organized in a vertical manner along sectors, and they
are structured hierarchically. Communication and cooperation between Departments
is usually sketchy. This often leads to duplication of efforts and
incompatibilities, the same old maps are being digitized over and over again by
various institutions, but they do it according to different or no standards, so
nothing fits together in the end.
At any administrative level, the necessary
coordination can be accomplished by establishing a steering committee and a
coordinating agency or better: a coordinating inter-agency-committee at the
technical level. In both bodies, the users should be represented prominently.
The full backing of the supreme decision-making body at the respective
administrative level is essential.
Application
What kind of usage can be made from a regional geographic
information infrastructure? This question can be answered from three different
perspectives: GIS, science, and general development.
GIS
perspective
From the relatively narrow perspective of the GIS profession,
it can be said that an organised geographic information infrastructure would
make GIS applications much more viable than they are now. We still spend around
80% of the money and time in any typical GIS project on building the database,
and very little effort can go into analysing the data and putting the finding
into action. Moreover, the time required to come out with some findings is
usually measured in years rather than days – much more than any policy-maker can
wait. Be efficiently using existing data, we could reduce this money and time
investment significantly, and thus bringing GIS from the academic into the
policy and business realms.
Science perspective
Scientists
interested in the HKH region face the problem that the region as a whole is
hardly a feasible unit of analysis. Hence they turn to case studies, where
detailed process research is undertaken at large scales. However, this brings
about two important issues: Selection of representative areas for case studies,
and generalising the findings (‘upscaling’). In both these tasks a comprehensive
geospatial database of the region would be very helpful.
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