Geospatial data are increasingly available nowadays, and this leads to more analyses and visualisation of geospatial data from several sources. To enable this, we need homogenous data as well as proper integration methods. Geospatial data integration has been a longstanding research topic for decades, and this paper discusses the utilisation of Linked Data technology stack to alleviate the geospatial data integration, particularly in the multi-scale context. Furthermore, this paper also discusses the possibilities of incorporating symbolisation information in Linked Data along with the integrated linked geospatial data for visualisation.
The rapid development of the Internet, together with the incentives from legislation, commence, and the open data trend, has led to the improvement of the availability of geospatial data, including both the authoritative geospatial data accessible from governmental Spatial Data Infrastructures (SDIs) and the prevalent Volunteered Geographic Information (VGI). For example, in Europe, the INSPIRE1 directive formulated that in a few years’ time, several authorities that are responsible for creating and maintaining geospatial data are obliged to set up download services to facilitate the access and sharing of geospatial data. The substantial improvement of data availability will enable crossdata set analysis and visualisation, in which the integration of geospatial data from different sources is indispensable.
The productions of geospatial data from different
sources are generally isolated, and this causes the
syntactic and semantic heterogeneity that are two
significant obstacles for geospatial data integration.
Furthermore, the links between multi-source
geospatial data that are of relevance are often
lacking. The absence of links between data sets
impedes the integration of geospatial data for
visualisation and analysis, and this impediment is
especially significant in a multi-scale environment.
For example, in a map mashup (a common form of
web map), the thematic data are usually simply
overlaid on the top of a base map without explicit
links and integration. However, the scales of the
thematic data and the base map are generally not
synchronised because unlike the thematic layer, the
base map is usually a multi-scale map from an
authoritative mapping agency and has multiple
representations
In this context, the Semantic Web technologies,
particularly the ones concerning Linked Data,
provide a promising technical framework to ease
the integration and linking between geospatial data.
“Linked Data” is the term for the collection of
design principles and technologies centred around a
paradigm to publish, retrieve, reuse, and integrate
data on the Web
• How to organise geospatial data in different scales in Linked Data, the design of unique resource identifiers and ontologies is important to link the multiple representations of each geographic object; • How to establish the links between different geospatial Linked Data sets, particularly in a multiscale context;
• How the links between data sets can be utilised for the synchronisation of scales between multisource geospatial data sets;
• How the linked geospatial data sets should be visualised and symbolised, namely how the symbolisation information should be defined and organised, and on which level (feature level, feature collection level, etc.) it should be defined.
• How the linked geospatial data sets would benefit the SDI. 2 2.1
in the geospatial domain where geometric,
topological as well as semantic information are
used
In the abovementioned environment of map mashup, in which multi-source geospatial data are generally simply overlaid together without any links established between each other, the integration usually is about multi-scale data sets. Stern and Sester (2013) studied mashups of natural protected areas on top of a base map, where the protected areas often have common geometries with the base map. To overcome the problem of inconsistencies in the multi-scale representation, they argued that the base map should act as constraints for generalising the thematic data. Toomanian et al. (2013) used Semantic Web technologies to integrate multi-source data in map mashups. They defined the semantic relationships between feature types in the thematic data and the base map in the map mashups using ontologies. These semantic relationships were then used to enable real-time adjustment of the thematic features to the base map.
Linked Data technology has been adopted to
facilitate geospatial data integration in some other
studies. For instance, Wiemann and Bernard (2016)
investigated possibilities for the integration of SDI
and Linked Data paradigm in terms of spatial data
integration. They implemented a prototype system
where the spatial relationships were explored by the
OGC Web Processing Service (WPS) and then
explicitly and separately stored using Linked Data,
including the information of involved features,
relationship types and conducted relationship
measurements.
In the framework of Linked Data technology,
some techniques have been extended in order to
improve the handling of linked geospatial data. For
example, SPARQL, as the query protocol for RDF,
has a standardised geospatial extension –
GeoSPARQL (Perry and Herring, 2011).
GeoSPARQL also provides an ontology as a
standardised exchange basis for geospatial RDF
data
The linked geospatial data are situated at rather
central places in the LOD because geospatial and
location data often serve as nexus and linkage
between different data items and sets
There have been some studies using ontologies to
organise and semantically annotate the symbology
information in Linked Data. For example, the OGC
(Open Geospatial Consortium) explored semantic
mediation of portrayal information of geospatial
data using ontology in their testbed 11 and 12
The Linked Data technology will be leveraged in this project. Specifically, the data will be constructed upon their connections with the reference data sets. For example, the natural protected areas are generally defined by their connections with other geographic objects (e.g., river, lake, road, etc.). Assuming that the reference geospatial data that have the topographic and cadastral objects are released in Linked Data, then the natural protected areas can be defined upon their relations with the objects in base map, and the scales between the reference data and the thematic data that are built upon the reference data can be automatically synchronised. Several case studies will be performed to verify the feasibility of the approach. In addition to this, the symbolisation information of both thematic and reference data will also be incorporated into the Linked Data sets to enable tailored visualization. The symbolisation of thematic data also can be dependent on the styling or other information in reference data.
To realise this idea, we need: • Multiple representation databases that are released as Linked Data to serve as reference data sets, the GeoSPARQL can be employed to act as vocabulary for geometries; and the design of URI still needs to be explored; • Ontologies that define the formal semantics of the relations between thematic and reference data, these can be extended from GeoSPARQL; • Ontologies that define the styling information of linked geospatial data, some concepts from SE and SLD can serve as reference; • A mechanism for generating thematic data from the relations with reference data for visualisation and analysis; • A prototypical system that can automatically generate thematic data from the above data modelling and visualise them according to the tailored symbolisation information.
The PhD study of the Weiming Huang at GIS Centre, Lund University is jointly funded by China Scholarship Council (CSC) and Lund University.
1.https://inspire.ec.europa.eu/ 2.http://www.geonames.org/ Stern, C. and Sester, M. (2013) Deriving constraints for the integration and generalization of detailed environmental spatial data in maps of small scales. In ICA Workshop on Generalisation and Multiple Representation, 23–24 August Dresden, Germany. Toomanian, A., Harrie, L., Mansourian, A. and Pilesjo, P. (2013). Automatic integration of spatial data in viewing services. Journal of Spatial Information Science, 2013(6), 43-58.