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spatial dimensions, time has to be taken into account as an
additional factor in this scenario. Messages are related to events
that occur at a definite point of time (e.g. an accident) or take
place during a certain time interval (e.g. the amount of time that
a fire-engine needs to get to the location of an accident).
Additionally, new messages do not necessarily provide newer or
more accurate or complete information.
incoming messages can be highly redundant, but this
redundancy is desired to fill gaps in the knowledge base. In
order to handle incompleteness and fuzziness of the messages,
semantic networks will be combined with Bayesian networks in
future works.
Figure 5. Messages with information at different spatial
resolution: single locations (level crossing A, building B), linear
features (streets D, E, F), large areas (district C).
6. CONCLUSIONS
This paper presented the ongoing work in a project about
textual and graphic representation. It was shown that both
representation schemes are closely connected and two example
applications were presented where both representations and
their relationship are essential parts of the given tasks. First
results of the Brazilian cadastre demonstrate that a common
symbolic representation of maps and texts can be established
(here as semantic network), enabling a full exploitation of both
knowledge resources. Further research in this project will be
concerned with a more detailed analysis of the questions raised
in section 4.3, especially in the context of analysing systems for
messages within disaster management.
x
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ACKNOWLEDGEMENTS
This work is supported by the Deutsche
Forschungsgemeinschaft (DFG), project no. BA 686/16.
