A schema matching method for the semantic integration of spatial data

2014 ◽  
Author(s):  
Qiang Wang ◽  
Huarui Wu ◽  
Huaji Zhu
Keyword(s):  
Spatial Data ◽  
Semantic Integration ◽  
Schema Matching ◽  
Matching Method

scholarly journals A Survey of Appliactions and Researches on Schema Matching between GIS Spatial Data

2015 ◽  
Vol XL-7/W4 ◽  
pp. 175-179
Author(s):  
Y.-H. Wang ◽  
H.-B. Zhang ◽  
J. Xu
Keyword(s):  
Spatial Data ◽  
Fundamental Problem ◽  
Schema Matching ◽  
Matching Task ◽  
Semantic Query ◽  
Matching Efficiency ◽  
Spatial Data Integration ◽  
Capability Evaluation ◽  
Manual Performance

As a fundamental problem of data management and application technology, schema matching has aroused the universal concern of the academic circles worldwide in recent years. In order to deepen the understandings of schema matching between spatial data and to identify its uses, the documentation method is adopted in this paper to firstly summarize and describe the foundation position and guidance role of schema matching in some typical applications such as spatial data integration (including schema-level integration and instance-level integration), updating information propagation, semantic query and handling, web geo-service finding. Then, aiming to the manual performance limitations of schema matching task in most systems, the previous works on schema matching are discussed mainly from four aspects of matching implementation approaches, matching efficiency optimization, matching results representation and matching capability evaluation for designing an automated approach and system. The related theories, models, approaches, limitations and new trends of current researches on schema matching are respectively analyzed. The conclusion is drawn by these analyses that schema matching researches are still faced with many theoretical and technological problems, the matching between schemas of spatial data will be more difficult and severe, and thus needs further studies since they are more heterogeneous, vaster and complex in structure than schemas of common data.

A LEXICAL DECISION TREE SCHEME FOR SUPPORTING SCHEMA MATCHING

2011 ◽  
Vol 10 (03) ◽  
pp. 519-537 ◽  
Author(s):  
BEEN-CHIAN CHIEN ◽  
SHIANG-YI HE
Keyword(s):  
Decision Tree ◽  
Lexical Decision ◽  
Structural Similarity ◽  
Schema Matching ◽  
Similarity Matching ◽  
Matching Method ◽  
Matching Algorithm ◽  
Essential Step ◽  
Structure Similarity ◽  
Two Phases

To manipulate semantic web and integrate different data sources efficiently, automatic schema matching plays a key role. A generic schema matching method generally includes two phases: the linguistic similarity matching phase and the structural similarity matching phase. Since linguistic matching is an essential step for effective schema matching, developing a high accurate linguistic similarity matching scheme is required. In this paper, a schema matching approach called Similarity Yield Matcher (SYM) is proposed. In SYM, a lexical decision tree is presented to determine the linguistic similarity matching of the first phase. A structural matching algorithm is then proposed to find the structure similarity between two tree schemas. The proposed schema matching approach was evaluated by testing on several benchmarks of real schemas and comparing with other methods. The experimental results show that the proposed lexical decision tree substantially improves the linguistic similarity matching effectively and efficiently. The proposed SYM algorithm also performs high effectiveness on 1–1 schema matching.

Using Federated Catalogs to Improve Semantic Integration among Spatial Data Infrastructures

2011 ◽  
Vol 15 (5) ◽  
pp. 707-722 ◽  
Author(s):  
Fabio Gomes de Andrade ◽  
Cláudio de Souza Baptista ◽  
Fabio Luiz Leite Jr
Keyword(s):  
Spatial Data ◽  
Semantic Integration ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures

scholarly journals Optimization of data integration using schema matching of linguistic-based and constraint-based in the university database

2021 ◽  
Vol 11 (3) ◽  
pp. 119-129
Author(s):  
Rifqi Hammad ◽  
◽  
Azriel Christian Nurcahyo ◽  
Ahmad Zuli Amrullah ◽  
Pahrul Irfan ◽  
...  
Keyword(s):  
Information System ◽  
Information Systems ◽  
Data Integration ◽  
Data Entry ◽  
Optimization Process ◽  
Schema Matching ◽  
Matching Method ◽  
Integration Problems ◽  
The University

University requires the integration of data from one system with other systems as needed. This is because there are still many processes to input the same data but with different information systems. The application of data integration generally has several obstacles, one of which is due to the diversity of databases used by each information system. Schema matching is one method that can be used to overcome data integration problems caused by database diversity. The schema matching method used in this research is linguistic and constraint. The results of the matching scheme are used as material for optimizing data integration at the database level. The optimization process shows a change in the number of tables and attributes in the database that is a decrease in the number of tables by 13 tables and 492 attributes. The changes were caused by some tables and attributes were omitted and normalized. This research shows that after optimization, data integration becomes better because the data was connected and used by other systems has increased by 46.67% from the previous amount. This causes the same data entry on different systems can be reduced and also data inconsistencies caused by duplication of data on different systems can be minimized.

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