Geography Reference
In-Depth Information
7 Conclusion and Future Work
In this paper, we proposed a conceptual framework and methodology that would
allow analysis of events and places using geotagged photo collections. We defined
four main types of spatio-temporal clusters that can be classified by time series
analysis and refined by semantic enrichment process using temporal component:
stationary, reappearing, occasional and regular moving. We discussed methods
for analysis of these types of clusters and identified publicly available datasets that
can help in the semantics enrichment process. We stressed the importance of the
interactively driven analysis that can overcome weaknesses of the purely auto-
matic approaches and help extracting new knowledge from the data. With the
example from the selected regions in Switzerland, we showed how time-series
analysis, text clustering and additional contextual information can be applied to
extract semantics and interpret the region under investigation.
Currently, parts of the framework are implemented as separate services. In our
next work, we will build a visual analytics framework integrating the methods
proposed in this paper. It will facilitate the discovery and interpretation of the
types of spatio-temporal clusters that we defined.
Acknowledgments This work was partially funded by the German Research Society (DFG)
under grant GK-1042 (Research Training Group ''Explorative Analysis and Visualization of
Large Information Spaces''), and by the Priority Research Program on Visual Analytics (SPP
1335), project ''Visual Spatio-temporal Pattern Analysis of Movement and Event Data''.
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