Data conversion method for semantic annotation of spatial data

Method for Bidirectional Conversion between Spatial Data RDB and RDF Using an XML Intermediate Model

This technology is a data conversion method that extracts spatial data containing semantic annotations, such as latitude and longitude, using SQL or SPARQL, maps it to an XML data model, and then converts it between RDB and RDF formats via extended XML and XSD schema files.

To connect spatial data in systems like GIS, semantic annotations had to be expressed as RDF-based triples. However, the difficulty of moving between data built separately in RDB and RDF formats has historically limited the scope of inference systems.

By using XML as a common intermediate format, this technology enables indirect conversion between RDB and RDF while preserving attributes such as weather, city names, country codes, and population. It can be applied to GIS and semantic web-based spatial inference services, allowing location data scattered across heterogeneous repositories to be integrated into a single knowledge base to enhance inference capabilities.

‍

‍

Key Features:

• Extracting data and metadata using SQL-based queries for RDB format data and SPARQL for RDF format data
• Mapping and converting the extracted data and metadata into an XML data model as a common intermediate format
• Storing the converted data as an extended XML file and the metadata and data structure information as an XML schema file with an extended XSD
• Indirectly converting semantic annotation data, including latitude and longitude, between RDB and RDF via XML

‍