Spatial information dissemination is a necessary step to make use of spatial information for which is a bridge between
the acquirement and the application of spatial information. However, conventional methods of spatial information
dissemination cannot cater to users in that not only users' personalized requirements cannot be satisfied, but initiative
dissemination service cannot be provided. In this paper, the idea of intelligent spatial information dissemination (ISD) is
proposed. Combining the ideas of personalized information retrieval, information filtering and recommender systems,
the ISD system employs user profiles and query conditions to provide two implement ways of spatial information
disseminations, namely "pull" and "push". Then, the three layers architecture of intelligent spatial information
dissemination system based on user profile model is given, and the procedure of data in the ISD system is introduced.
Also, the user profile is presented including user profile model and user profile management. Finally, the prototype
system of intelligent spatial information dissemination is presented.
KEYWORDS: Information fusion, Chemical elements, Associative arrays, Standards development, Data modeling, Roads, Remote sensing, Geographic information systems, Artificial intelligence, Telecommunications
Metadata is important to facilitate data sharing among Geospatial Information Communities in distributed environment. For unanimous understanding and standard production of metadata annotations, metadata specifications are documented such as Geographic Information Metadata Standard (ISO19115-2003), the Content Standard for Digital Geospatial Metadata (CSDGM), and so on. Though these specifications provide frameworks for description of geographic data, there are two problems which embarrass sufficiently data sharing. One problem is that specifications are lack of domainspecific semantics. Another problem is that specifications can not always solve semantic heterogeneities. To solve the former problem, an ontology-based geographic information metadata extension framework is proposed which can incorporate domain-specific semantics. Besides, for solving the later problem, metadata integration mechanism based on
the proposed extension is studied. In this paper, integration of metadata is realized through integration of ontologies. So
integration of ontologies is also discussed. By ontology-based geographic information semantic metadata integration,
sharing of geographic data is realized more efficiently.
Conventional spatial information delivery is system-oriented, and users have to adapt to the system and complete the
delivery of spatial information. Two disadvantages exist in the delivery service mode: (1) users' personalized
requirements cannot be satisfied; (2) Initiative delivery service cannot be provided for users. In this paper, we firstly
classify conventional user profile models into four categories. After analyzing the limitations of these user profile models,
we conclude that conventional user profile models are not suitable for the application of spatial information intelligent
delivery. Then, aiming to the objectives of spatial information intelligent delivery, we propose a user profile model of
spatial information, and give the building method of the model. Also, we put forward a similarity measure method
between spatial information and user profile. In order to verify the availability of the user profile model, we present an
example of spatial information intelligent delivery. The experimental results show that the proposed user profile model
can reflect user profile quite well.
KEYWORDS: Databases, Geographic information systems, Distributed computing, Optimization (mathematics), Analytical research, Data modeling, Remote sensing, Data processing, Signal processing, Information operations
Geographic Information System (GIS) is moving towards distribution and sharing. Distributed Spatial Database Systems
(DSDBS) has attracted the attention of many scholars. This paper introduces the prospects of Distributed GIS (DGIS),
and describes the definition of DSDBS and the existing problems. The researches in related fields are analyzed, including
the research results in the traditional distributed relational database fields, the distributed spatial database fields and the
spatial query optimization aspect. Grid technologies are developing forward, and grid will be turned into the standard
distributed computing platform, therefore the application of DSDBS will be much broader than ever. The present studies
on distributed spatial query focus on spatial join optimization. Researches on query scheduling are rare. In the process of
constructing our test system for distributed spatial query, we find there are some replication nodes after the step of data
localization. These nodes cause redundant computing of query processing. This paper gives a method to solve it based on
the Query Scheduling Tree Model (QSTM). It also gives a detailed scheduling algorithm, and analyzes the effectiveness
of the model and the algorithm.
KEYWORDS: Geographic information systems, Data storage, Data conversion, Data modeling, Standards development, Databases, Software development, Visualization, Computing systems, Remote sensing
Spatial data sharing among multiple GIS (Geographic Information System) platforms is a fundamental requirement of many GIS applications, yet conventional methods of spatial data interoperability don't adequately consider practical application circumstance, which now becomes a primary barrier to more efficient spatial data sharing among multiple GIS platforms. In this paper, after analyzing the disadvantages of conventional methods and the causation of the disadvantages, and analyzing the principle of spatial data access of ArcGIS, MapInfo and GeoStar based on Oracle Spatial storage, the authors propose a new spatial data interoperability method called Different meta information and Same spatial data Method. This method is based on Oracle Spatial, through which spatial data interoperability for multi-platform of GIS is available. The results of experiments demonstrate that this method is a new simple practical approach adapted for current application circumstance, and it provides us a new idea for spatial data interoperability.
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