Abstract: Provided are techniques for testing quality of relationship discovery. Reference mappings and test mappings are received, wherein each of the reference mappings and test mappings includes one or more mappings, and wherein each of the mappings includes a mapping input and a mapping output, Each of the reference mappings and test mappings is parsed to generate a reference structure and a test structure, wherein the reference structure and test structure each contains entries with mapping outputs as keys matched with mapping inputs as values. The reference structure and the test structure are compared to determine the quality of relationships discovered in the test mappings.

Abstract: Provided are a method, system, and program for determining compliance of a database architecture to an enterprise data standard. A physical model is generated defining database elements in a database. A logical model is provided representing a definition of elements and their relationships. The logical model is used to generate a mapping of database element names in the physical model to corresponding elements in the logical model. The mapping and the logical model are processed to determine an extent to which the database elements and relationships in the physical model violate rules of the logical model.

Abstract: Various embodiments of a method, system and article of manufacture to discover relationships among a first set of elements and a second set of elements are provided. At least one metric algorithm is identified based on a metric selection parameter. A raw result is determined based on the at least one metric algorithm, a first specified structural description of the first set of elements and a second specified structural description of the second set of elements. The raw result comprises a plurality of relationship measurements and the raw result is ordered. In some embodiments, a balanced result is produced based on the raw result and a matching strategy algorithm. In other embodiments, the matching strategy algorithm is identified based on a matching strategy selection parameter.

Abstract: Techniques are provided for viewing mappings between objects. A main view is displayed, wherein the main view shows one or more source objects, one or more target objects, and zero or more mappings between the one or more source objects and the one or more target objects. Input selecting a type of view to be displayed in the main view is received, wherein each type of view provides a different amount of detail regarding the mappings. In response to receiving the input, the selected type of view is created, and the created view is displayed. Additionally, techniques are provided for viewing objects. One or more objects along with mappings between the one or more objects are displayed. View filters are provided that may be applied to the one or more objects, wherein the view filters enable hiding at least one of mapped or unmapped objects. Moreover, techniques are provided for viewing nodes. A structure is displayed that includes one or more nodes.

Abstract: A computer program product is provided that uses data examples as a basis for understanding and refining declarative schema mappings. The system of the present invention identifies a set of intuitive operators for manipulating examples including establishing value correspondences, data linking, data trimming, data walking, and data chasing. These operators allow a user to follow and refine an example by walking through a data source. In addition, these operators can identify a large class of schema mappings and distinguish effectively between alternative schema mappings. With these operators, a user is able to quickly and intuitively build and refine complex data transformation queries that map one data source into another while continuously verifying that the mapping is accurate and appropriate.

Abstract: Techniques are provided for semantic matching. A semantic index is created for one or more schemas, wherein each of the one or more schemas includes one or more word attributes, and wherein each of the one or more word attributes includes one or more tokens, wherein the semantic index identifies one or more keys and one or more values for each key, wherein each value specifies one of the one or more schemas, a word attribute from the specified schema, and a token of the specified word attribute, and wherein the specified token is a synonym of the key. For a source word attribute from one of the one or more schemas, the source word attribute is used as a key to index the semantic index to identify one or more matching word attributes.

Abstract: An apparatus and method are described for the discovery of semantics, relationships and mappings between data in different software applications, databases, files, reports, messages, or systems. In one aspect, semantics and relationships and mappings are identified between a first and a second data source. A binding condition is discovered between portions of data in the first and the second data source. The binding condition is used to discover correlations between portions of data in the first and the second data source. The binding condition and the correlations are used to discover a transformation function between portions of data in the first and the second data source.

Abstract: A computer program product is provided that uses data examples as a basis for understanding and refining declarative schema mappings. The system of the present invention identifies a set of intuitive operators for manipulating examples including establishing value correspondences, data linking, data trimming, data walking, and data chasing. These operators allow a user to follow and refine an example by walking through a data source. In addition, these operators can identify a large class of schema mappings and distinguish effectively between alternative schema mappings. With these operators, a user is able to quickly and intuitively build and refine complex data transformation queries that map one data source into another while continuously verifying that the mapping is accurate and appropriate.