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