Schema matching

The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects. For example, in the two schemas DB1.Student (Name, SSN, Level, Major, Marks) and DB2.Grad-Student (Name, ID, Major, Grades); possible matches would be: DB1.Student ≈ DB2.Grad-Student; DB1.SSN = DB2.ID etc. and possible transformations or mappings would be: DB1.Marks to DB2.Grades (100-90 A; 90-80 B: etc.). Automating these two approaches has been one of the fundamental tasks of data integration. In general, it is not possible to determine fully automatically the different correspondences between two schemas — primarily because of the differing and often not explicated or documented semantics of the two schemas. Among others, common challenges to automating matching and mapping have been previously classified in especially for relational DB schemas; and in – a fairly comprehensive list of heterogeneity not limited to the relational model recognizing schematic vs semantic differences/heterogeneity. Most of these heterogeneities exist because schemas use different representations or definitions to represent the same information (schema conflicts); OR different expressions, units, and precision result in conflicting representations of the same data (data conflicts). Research in schema matching seeks to provide automated support to the process of finding semantic matches between two schemas. This process is made harder due to heterogeneities at the following levels Syntactic heterogeneity – differences in the language used for representing the elements Structural heterogeneity – differences in the types, structures of the elements Model / Representational heterogeneity – differences in the underlying models (database, ontologies) or their representations (key-value pairs, relational, document, XML, JSON, triples, graph, RDF, OWL) Semantic heterogeneity – where the same real world entity is represented using different terms or vice versa Discusses a generic methodology for the task of schema integration or the activities involved.