Schema Matching for Semi-structured and Linked Data

The Linked Data paradigm is a common standard initiated to complement the general architecture of the semantic web and create a single space containing data that is machine-readable and connected to related data. Figures, however, show that one of the main sources of semi-structured data providers, Web APIs, continued to grow even after the creation of the Linked Data concept. Given that data sources with significant value are still in a semi-structured format, it is essential to bridge between the two data models, so that the full potential of the semantic web can be realised. This paper presents SimiMatch, an approach for schema matching between semi-structured and Linked Data. It contributes towards a virtual integration system that will be able to provide transparent access to heterogeneous and autonomous sources. It addresses the challenge of sustaining the continuous changes of the web of data via semantic similarity measurement.