Multi-Resolution Representation Using Graph Database
Date
2021-09-16
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Abstract
In the context of rapid development on mobile and internet services, volumes of geospatial data are also increasing enormously. Demands on geospatial information systems are no longer limited to more efficient data storage and retrieving, but also expand to faster querying and higher flexibility. Multi-resolution representation data is an important geospatial data resource for various research works and applications. With one spatial object represented by different geometries under different resolutions, multi-resolution representation data is usually more complex in the relationship and larger in size when comparing to single resolution ones. In addition, most of current approaches for multi-resolution representation data are either complex in structure, or time consuming in traversal and query. Besides, switching between different representations for one spatial instance is still intricate in most of the approaches, especially in topological map sets. A novel approach for storing, managing, and querying multi-resolution representation data is proposed. Development of the proposed approach is based on a popular graph database platform, Neo4j. Neo4j is advanced in flexibility since it allows user-defined structures. Benefited from its node-relationship structure as well as the powerful query language, Cypher, query within Neo4j is exceedingly readable and efficient, especially for join-style queries. Nevertheless, spatial visualization and operation are rather limited in Neo4j. On top of this, bridging by Neo4j Bolt Driver, a web-based interface is also developed to provide interactive spatial visualization and more diverse operations. Moreover, direct traversal between different representations for one spatial object (or groups of objects) is now available. Consequently, the well-structured system for multi-resolution representation data provides a reliable and intuitive database architecture and interface. Over and above that, this system truly closes the gap between complex data and novice users by simplifying various query operations.
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Keywords
Geographic Information System, Multi-resolution, Multi-representation, Graph Database;
Citation
Huang, Y. (2021). Multi-Resolution Representation Using Graph Database (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.