SEMANTIC DEFINITION AND MATCHING FOR NATIONAL
SPATIAL DATA INFRASTRUCTURE
Gülten Kara, Deniztan Ulutaş, Çetin Cömert,
Karadeniz Technical University, Trabzon, Turkey
In Turkey, the establishment of National Spatial Data Infrastructure (NSDI) is on the
agenda. The technologies which are still in use for technological infrastructure of any
SDI are “Syntactic Web” technologies. However, it is foreseen that in the near feature,
the current technologies will be replaced by “Semantic Web” technologies. This has
formed the motivation for this work which aimed at developing a methodology for
semantic definition of data of the participators of an NSDI.
One of the primary requirements of SW is the semantic definition of data and services.
The semantic definition is that syntactic definition of data and services is represented by
one of the semantic web languages and definition data and services is associated upper
ontology. In the related literature, several projects are fulfilled and studies have been
published. FinnONTO (National Semantic Web Ontology Project in Finland) Project1
started in 2003 and it is scheduled to complete in 2012. The goal of project is to lay a
foundation for a national metadata, ontology, ontology service, and linked data
framework in Finland. SWING (Semantic Web Services Interoperability for Geospatial
Decision Making) Project2 runs from 2006 to 2009. The objective of project is to
provide an open, easy-to-use SWS framework of suitable ontologies and inference tools
for annotation, discovery, composition, and invocation of geospatial web services.
ACE-GIS (Adaptable and Composable E-commerce and Geographic Information
Services) project (URL-1) started in June 2002 and was successfully completed in
October 2004. The project provides better and more efficient tools for development,
deployment, discovery and composition of distributed web-services with special
emphasis on the key combination of geographical information and e-commerce
services. Schade (2009) presented an approach for achieving computer-tractable
translation of geospatial data. Klien (2008) propose a method to automatically support
the semantic annotation process that evaluates the validity of existing annotations and
suggests possible new ones. Lemmens (2006) proposed semantic interoperability
framework serving semantic definition of spatial web services with Nen36103,
Top10NL4, RiskMap and Travel ontologies. Dolbear at al., (2005) addresses the
problem of integrating a data ontology, exactly describing the database schema of
the British national mapping agency, with an application ontology. The problem here
is how semantic definition of data and services will be made. In our previous work
(Kara, Cömert, 2011), we proposed the methodology to make semantic definition of the
participators of an NSDI.
The second requirement of SW is semantic annotation of data and services. Semantic
annotation is formal statement establishing a link between concepts in ontology and
features in a data source. This task requires upper ontologies. Since an upper ontology
1
FinnONTO Project, http://www.seco.tkk.fi/projects/finnonto/
SWING Project, http://138.232.65.156/swing/index.html
3 NEN3610, http://www.geonovum.nl/content/geonovum-0
4 TOP10NL, http://www.kadaster.nl/window.html?inhoud=/top10nl/
2
describes very general concepts, it has to be extended. In the related literature, several
ontology extension studies are available. Probst (2007) extended DOLCE5 for making
the meaning of symbols explicit that denote observation and measurement results. Klien
(2008) extended DOLCE for providing a classification schema of geographic objects.
Novaljia and Mladenić (2010) proposed a methodology for text-driven semi-automatic
ontology extension using Cyc ontology content and ontology structure information.
OntoPlus (URL-2) is a text-driven methodology for extending ontologies, using content,
structure and co-occurrence information. The OntoPlus methodology can extend large,
multi-domain ontologies, and is implemented as an interface for extending the Cyc
ontology using glossary files. One of the problems here is to determine what upper
ontology will be used. It is out of scope of this paper how the upper ontology is
evaluated. We select DOLCE ontology because its size is smaller than others (e.g.
SUMO6, Cyc7). Second problem is to identify the concept extended in the upper
ontology and how the procedure of ontology extension will be followed. We extend
DOLCE re-using part of Klien’s taxonomy and commit ourselves subcategories of
“ManMadeStructure”. We will continue to extend upper ontology for the GCM-Road
Ontology and INSPIRE-TN Ontology.
The other requirement of SW is semantic matching. If schemas thought as graph
structure, “Semantic Matching” can be perceived as concepts of two graph nodes
comparing semantically for determining the similarities between them. There are
various works related with semantic matching in the literature. In our schema matching
scenario, we used S-Match (Giunchiglia et al., 2004) software. S-Match takes two
schemas and returns semantic relations between the nodes of the schemas using
WordNet (URL-3) lexical database as an external resource. We can classify schema
matching technics with three groups. These are; schema based, instance based, external
resource based. S-Match fits both schema and external resource based class.
In our schema matching scenario, we converted Road Schema of General Command of
Matching8 and Transport Network (TN) Schema of INSPIRE (Infrastructure for Spatial
Information in Europe) to semantic web language using SWT (GCM-Road Ontology
and INSPIRE-TN Ontology). Then, we implemented semantic matching between GCMRoad Ontology and INSPIRE-TN Ontology with S-Match.
In our future work, we plan to make works to increase accuracy and amount of match
results. For this, in order to use in matching we plan to create a source like GeoWordNet
(URL-4) that contains Turkish spatial concepts, attributes and relations. As far as we
know, there isn’t available a resource like it in Turkey literature. And also, we will
make works about matching relations of schema entities. And we will go on works
about transformation between schemas.
5
DOLCE, http://www.loa.istc.cnr.it/DOLCE.html
SUMO, http://www.ontologyportal.org/
7 Cyc, http://www.cyc.com/
8
GCM is the National Mapping Agency for 1/25 000 and smaller scale maps in Turkey
6
REFERENCES
Dolbear C., Goodwin J., Mizen H., Ritchie J., 2005, Semantic interoperability between
topographic data and a flood defence ontology, Ordnance Survey Technical Report
I001.
Giunchiglia, F., Shvaiko, P., Yatskevich, M., 2004. S-MATCH: An Algorithm and An
Implementation of Semantic Matching, Technical report # DIT-04-015, February 2004,
Trento (Italy).
Kara, G., and Cömert, C., 2011. Semantıc Data Defınıtıon For Natıonal Spatıal Data
Infrastructure, Congress of Geographic Information Systems, 31 October - 04
November 2011, Antalya Culture Center, Antalya.
Klien, E. (2008). Semantic Annotation of Geographic Information. Institute for
Geoinformatics. Münster, Germany, University of Münster. PhD.
Lemmens, R. L. G., 2006. Semantic interoperability of distributed geo – services,
Netherlands Geodetic Commission NCG : Publications on Geodesy : New Series 63,
ISBN: 90-6132-298-7.
Novalija, I., Mladenic, D., 2010. Ontology Extension Towards Analysis of Business
News. Informatica (Slovenia) 34(4): 517-522.
Probst, F. (2007). Semantic Reference Systems for Observations and
Measurements, Institute for Geoinformatics. Münster, Germany, University of Münster.
PhD.
Schade, S., 2009. Ontology-Driven Translation of Geospatial Data, PhD Thesis,
Institute for GeoInformatics, University of Münster, Münster, Germany.
URL-1, ACE-GIS Project http://plone.itc.nl/agile_old/Conference/greece2004/papers/P11_Poveda.pdf, 11.10. 2010.
URL-2 OntoPlus, http://www.youtube.com/watch?v=9h9iZYGQ9P4, 20.12.2011.
URL-3 WordNet, http://wordnet.princeton.edu/, 22.12.2011
URL-4GeoWordNet,http://s-match.org/background-knowledge-datasets.html
23.12.2011
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