Fubao Zhu

Storing and querying GML in object-relational databases

GML has become the de facto standard for electronic spatial data exchange among the applications of Web and distributed geographic information systems (GISs). As more and more geographical data is presented in GML, it is necessary to develop techniques for managing GML documents in databases. A possible solution is to store GML data into object-relational databases from which the users can retrieve the interested data. In this paper, we propose an approach to map GML schema to object-relational database schema by using GML schema graph, and algorithms for storing / querying valid GML documents into / from the relations generated by the corresponding object-relational schema. Spatial and non-spatial features embedded in GML document are stored in object-oriented relations, and the structures and constrains defined in GML schema are also well preserved. A prototype for GML documents storing and querying based on the proposed method is implemented on the basis of the Oracle/Spatial system. Preliminary experiment results shows that our method is feasible and efficient.

Constraints-preserving GML storage in object-relational databases

As Geography Markup Language (GML) becomes a standard for geographic information representation on the internet, more needs to efficiently store and retrieve GML data arise. Storing and retrieving GML data in object-relational database is a proper option considering its sophisticated technology and object-oriented features. The existing storage approaches for GML are not satisfactory for they consider only data aspects while ignoring semantic constraints. In the paper, we explore the structure and semantic characteristics existed in GML, and present a method to capture and map these constraints into object-relational databases during GML storage. Comparing with the existing methods, our approach preserves not only the data and structure, but also its semantics of GML document.

Querying GML documents: An XQuery based approach

GML is an XML encoding for representation and exchange of geographic information. With the popularity of GML, more and more spatial data exists in GML format. It raises the problem of how to query the data in GML. Since GML is based on XML, query technologies for XML can be employed to GML. However, the fact that GML differs from XML in many aspects makes these technologies not so applicable for GML. The standard query language XQuery, which is recommended by W3C, only applies to GML non-spatial queries. To query GML documents, we propose a GML query processor by extending XQuery in datatypes and spatial operators. The processor can deal with non-spatial and spatial queries, and output the query results in GML format.

Ontology-based semantic integration of GML spatial information

GML is an XML encoding for the modeling, transport and storage of geographic information, which has been making a significant influential on the ability of organizations to share geographic information among their Web based GIS applications. Ontology has been acknowledged to be the kernel methodology for capturing and sharing semantics of spatial information. This paper proposes a framework for integrating spatial information based on GML schema matching by using ontology technologies, in which GML is adopted as the common format for spatial information wrapping and mediation, and ontology is used to overcome the heterogeneity when matching different GML schemas. A prototype is also implemented based on the proposed framework.

LRIR: A hybrid semantic Web services matching approach

Web services discovery is one of major processes of the Service-Oriented Architecture and the services matching algorithm plays an important role in the service discovery process. Some semantic matching algorithms have been proposed in order to overcome the drawbacks of the syntax-based techniques. In this paper, we propose a hybrid semantic Web service matching algorithm, called LRIR, that combines logic based reasoning with syntactic text based similarity. Experimental results show that the proposed hybrid approach outperforms the existing techniques purely based on logic reasoning or text similarity.

Gstruct : a system for extracting schemas from GML documents

Geography Markup Language (GML) becomes the de facto standard for geographic information representation on the internet. GML schema provides a way to define the structure, content, and semantic of GML documents. It contains useful structural information of GML documents and plays an important role in storing, querying and analyzing GML data. However, GML schema is not mandatory, and it is common that a GML document contains no schema. In this paper, we present Gstruct, a tool for GML schema extraction. Gstruct finds the features in the input GML documents, identifies geometry datatypes as well as simple datatypes, then integrates all these features and eliminates improper components to output the optimal schema. Experiments demonstrate that Gstruct is effective in extracting semantically meaningful schemas from GML documents.