The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XL-7/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W4, 175–179, 2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W4, 175–179, 2015

  26 Jun 2015

26 Jun 2015

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

Y.-H. Wang1, H.-B. Zhang1, and J. Xu2 Y.-H. Wang et al.
  • 1School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, China
  • 2School of Economics and Management, Henan Polytechnic University, Jiaozuo, China

Keywords: Implementation Approach, Efficiency Optimization, Result Representation, Capability Evaluation

Abstract. 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.