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The proliferation of GPS-enabled devices and their utilisation by users for
geo-tagging personal resources, actions and interactions on the Web is
leading to the accumulation of a new type of information on individual users
and user groups. The
accumulation of spatiotemporal (ST) user footprints on the Social Web
provides an opportunity for deriving personal profiles for users that
closely reflect users’ interests over space and time.
This research area concerns the extraction and making sense of such
profiles to enhance users’ Web interaction experience.
Geographic Information
Retrieval
When people search for information on the web it is very common to specify a
geographical location. The need to match people's requirement for
geographically-specific information with the numerous sources of
geographically referenced information has spurred the development of
geographical and location-aware information retrieval facilities. This is
reflected in the presence of geographically-specialised or so-called "local"
search facilities associated with the main web search engines as well as the
provision of location-sensitive information services on mobile devices.
There are many challenging research problems to be addressed in order to
make geographical and location-aware search facilities genuinely effective.
These are concerned for example with determining the geographical context of
text documents in which terminology is often vague and ambiguous, building
global geographical knowledge bases, indexing documents with respect to both
geographical context and textual content, interaction with spatially-aware
search devices, and geographical relevance ranking.
Visualization of
Geo-Spatial Linked Data
The Web is increasingly becoming a global information space consisting not
just of linked documents, but also of linked data.
This emerging Web of Data now includes diverse data sets, such as
DBpedia, GeoNames and Flickr.
This area of research is concerned with the exposure of the inherent
geo-spatial and temporal content of linked data resources in view of using
this information as an anchor for linking and integrating different data
sets. In particular,
visualisation techniques will be explored to allow for the interpretation of
the RDF graphs underlying the data resources.
Visualisation of both the spatial and temporal dimensions of the data
will allow for the exposure of the inherent spatial, temporal and thematic
relationships between data objects and can thus allow for the comparison of
multiple data resources and facilitate their integrated utilisation by
users.
Supporting qualitative data and analysis is a longstanding concern within
Geographic Information Science, evident in ongoing research on ways of
handling qualitative spatial expressions with spatial databases as well as
efforts to blend GIS with qualitative research, as part of mixed methods
research practices. This
research area aims to investigate methods of extending current GIS
technologies to model and manipulate the notion of Place, as conceptualized
and required for enabling mixed-method research within GIS.
Use cases in the area of social geography shall be sought to support
and evaluate this research.
Spatio-temporal Data
Modelling
Large spatial databases are characterised by two main features: the large
set of spatial objects of different shapes to be stored, and the inordinate
number of spatial relationships (of different types) between those objects.
These features impose a substantial burden on storage overheads and system
performance which necessitates an efficient mechanism to represent such
relations in spatial queries. One of the aims of this research is to design
and implement a system for the representation of and reasoning over
different types of spatial relationships between objects of arbitrary
complexity. Work is also ongoing on modelling of the notion of change in
spatio-temporal databases.
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This site was last updated 11/20/14
