Search results
Results from the WOW.Com Content Network
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.
The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term " schema " refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases ).
Record linkage (also known as data matching, data linkage, entity resolution, and many other terms) is the task of finding records in a data set that refer to the same entity across different data sources (e.g., data files, books, websites, and databases).
Semantic matching is a technique used in computer science to identify information which is semantically related. Given any two graph-like structures, e.g. classifications , taxonomies database or XML schemas and ontologies , matching is an operator which identifies those nodes in the two structures which semantically correspond to one another.
A schema crosswalk is a table that shows equivalent elements (or "fields") in more than one database schema. It maps the elements in one schema to the equivalent elements in another. It maps the elements in one schema to the equivalent elements in another.
Ontology merging defines the act of bringing together two conceptually divergent ontologies or the instance data associated to two ontologies. This is similar to work in database merging (schema matching). This merging process can be performed in a number of ways, manually, semi automatically, or automatically.
From January 2008 to December 2012, if you bought shares in companies when Patricia A. Woertz joined the board, and sold them when she left, you would have a -6.6 percent return on your investment, compared to a 2.6 percent return from the S&P 500.
An SQL schema is simply a namespace within a database; things within this namespace are addressed using the member operator dot ".". This seems to be a universal among all of the implementations. A true fully (database, schema, and table) qualified query is exemplified as such: SELECT * FROM database. schema. table