ONTOLOGY-BASED SEMANTIC DESCRIPTION MODEL FOR DISCOVERY AND
RETRIEVAL OF GEO SPATIAL INFORMATION
Qin Zhan a , Xia Zhang b , Deren Li c
a School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
- qin.zhan@gmail.com
b Printing and Packaging School, Wuhan University, 129 Luoyu Road, Wuhan 430079, China - zxx@whu.edu.cn
c State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University,
129 Luoyu Road, Wuhan 430079, China - dli@wtusm.edu.cn
KEY WORDS: GIS, Integration, Knowledge Base, Retrieval, Representation, Spatial Infrastructures, Model, Method
ABSTRACT:
Finding and accessing suitable geographic information to satisfy various applications in the open and distributed environments of
Spatial Data Infrastructures (SDIs) is a crucial task. However, because of the semantic heterogeneity in conventional exploitations
and descriptions of geographic information, it is difficult to find suitable geographic information which exactly meets the
requirements of application. To solve the problems caused by semantic heterogeneity, this paper presents an ontology-based
semantic description model which explicitly represents geographic information semantics in abstract and concrete level. It is an
integrated model consisting of three parts: Data Profile, Data Content, and Data Binding. Data Profile tells users what the data are
about in abstract level. Data Content describes what the data contain in concrete level. Data Binding tells users where and how to
access the data. Moreover, this paper puts forward an ontology based approach to enhance the efficiency of discovery and retrieval
of geographic information.
1. INTRODUCTION
Geographic information (GI) is more and more important in
various application domains such as planning and decision
making etc. Finding and accessing suitable geographic
information to satisfy these applications in the open and
distributed environments of Spatial Data Infrastructures (SDIs)
is a crucial task. However, it is difficult to find suitable
geographic information which exactly meets the requirements
of application because of the semantic heterogeneity in
conventional exploitations and descriptions of geographic
information. Much research work has been done for discovery
and retrieval of geographic information by OpenGIS
Consortium (OGC). The specifications provided by OGC
enable the syntactic interoperability and cataloguing of
geographic information. Though the catalogs support
discovering, organization, and access of geographic
information, they do not yet provide methods to solve problems
of semantic heterogeneity (Bernard et al., 2004; Klien et al.,
2004). Problems of semantic heterogenity are caused by
synonyms and honmonyms in metadata and user’s query (Klien
et al., 2004). This is because various metadata specifications
and various vocabularies are used in metadata and user’s
queries. In various specifications and vocabularies, different
terms may refer to similar concepts, and the same terms may
refer to different concepts. So overcoming problems of
semantic heterogeneity is the key to enhance efficiency of
discovering and retieval of geographic information.
One possible approach to overcome the problems of semantic
heterogeneity is the explication of knowledge by means of
ontology, which can be used for the identification and
association of semantically corresponding concepts because
ontology can explicitly and formally represent concepts and
relationships between concepts and can support semantic
reasoning according to axioms in it. Ontology has been
developed in the context of Artificial Intelligent (AI) to
facilitate knowledge sharing and reuse. It covers many fields
such as knowledge engineering, information integration,
information retrieval and so on. The reason for ontology being
so popular is due to what it promises: a shared and common
understanding of some domain that can be communicated
between people and application systems. Many definitions of
ontology have been proposed. A popular definition of them is:
an ontology is a formal, explicit specification of a shared
conceptualization (Gruber, 1995). The meanings of the
definition is explained (Studer et al., 1998): A
“conceptualization” refers to an abstract model of some
phenomenon in the world by having identified the relevant
concepts of that phenomenon; “Explicit” means that the type of
concepts used, and the constraints on their use are explicitly
defined; “Formal” refers to the fact that the ontology should be
machine readable; “Shared” reflects the notion that an ontology
captures consensual knowledge, that is, it is not private to some
individual, but accepted by a group.
In this paper, an ontology-based semantic description model is
put forward to explicitly represent geographic information
semantics in abstract level and concrete level by introducing
ontologies. It is an integrated model consisting of three parts:
Data Profile, Data Content, and Data Binding. According to the
model, descriptions of geographic information can be readable
and understandable for computers. Moreover, based on the
proposed model, an ontology-based approach is discussed to
enhance efficiency of discovering and retrieval of geographic
information.
This paper is organized as follows. In section 2, we make a
survey on the related works. Then, the ontology-based
semantic description model is presented in section 3. In the
subsequent section, the ontology-based approach for