System and Data Integration’
System and Data integration involves combining data residing in different sources and providing users with a unified view of these data. This process becomes significant in a variety of situations, which include both commercial (when two similar companies need to integrate their databases) and scientific (combining research results from different bioinformatics repositories, for example) domains.
Issues with combining heterogeneous data sources under a single information systems have existed from the ‘Data Warehoue Era.’The ETL (Extract, Transforms, and Loads)process in enterprise extracts information from the source satabases, transforms it and loads into the data warehouse. ETL process makes the data from heterogeneous sources become compatible with each other under signel enterprise system.
However, this is just starting point of needs for view integration for heterogeneous data source. We have faced with more complex and various situation of system integration. To solve the problem related to system/data integration situation, our research have dealt with various subtopics shown below.
Semantic Integration of Information Systems
- Ontology-based Approach
- Computational linguistics-based Approach (especially, corpus linguistics)
- Semantic query processing
- Structural matching based on graph theory
- Strategy for dyanamic matcher selection
- Semantic schema matching