Abstract: Methods, systems, and computer program products for constraint tracking and inference generation are provided herein. A computer-implemented method includes parsing descriptions of one or more user-provided constraints pertaining to data within a target system, parsing truth value assignments to the user-provided constraints, and deriving a truth value for at least one of the user-provided constraints that does not correspond to a known truth value, wherein said deriving comprises performing a logical inference utilizing known truth values of one or more of the user-provided constraints. The computer-implemented method also includes storing, in a database, (i) the user-provided constraints, (ii) the known truth values, and (iii) the at least one derived truth value, and outputting the at least one derived truth value, one or more identified contradictions among the known truth values, and/or an indication that one or more unknown truth values corresponding to the user-provided constraints remain unknown.

Abstract: Methods, systems, and computer program products for constraint tracking and inference generation are provided herein. A computer-implemented method includes parsing descriptions of one or more user-provided constraints pertaining to data within a target system, parsing truth value assignments to the user-provided constraints, and deriving a truth value for at least one of the user-provided constraints that does not correspond to a known truth value, wherein said deriving comprises performing a logical inference utilizing known truth values of one or more of the user-provided constraints. The computer-implemented method also includes storing, in a database, (i) the user-provided constraints, (ii) the known truth values, and (iii) the at least one derived truth value, and outputting the at least one derived truth value, one or more identified contradictions among the known truth values, and/or an indication that one or more unknown truth values corresponding to the user-provided constraints remain unknown.

Abstract: One embodiment provides a method including: receiving input indicating at least one concept from at least one document of an input document collection; generating a validated data model for each of a plurality of concepts, wherein each of the concepts is represented as a visual data structure comprising semantics; generating at least one intermediate model object by parsing the validated data model, wherein each of the intermediate model objects comprises a concept object and the at least one intermediate model object identifies concept dependencies; translating the at least one intermediate model object into executable source code by importing at least one pre-built extractor and translating at least one rule identified from the visual data structure; and generating an executable information extraction program from the executable source code, wherein the generating comprises generating at least one rule for the executable information extraction program based on the identified concept dependencies.

Abstract: One embodiment provides a method including: receiving input indicating at least one concept from at least one document of an input document collection; generating a validated data model for each of a plurality of concepts, wherein each of the concepts is represented as a visual data structure comprising semantics; generating at least one intermediate model object by parsing the validated data model, wherein each of the intermediate model objects comprises a concept object and the at least one intermediate model object identifies concept dependencies; translating the at least one intermediate model object into executable source code by importing at least one pre-built extractor and translating at least one rule identified from the visual data structure; and generating an executable information extraction program from the executable source code, wherein the generating comprises generating at least one rule for the executable information extraction program based on the identified concept dependencies.

Abstract: One embodiment provides a method for generating an executable extraction program from a visual representation, the method including: utilizing at least one processor to execute computer code that performs the steps of: obtaining a validated model comprising a plurality of concepts, wherein each of the concepts comprises semantics associated with a visual representation of an object; generating at least one intermediate model object by parsing the validated model, wherein each of the intermediate model objects comprises a concept object; translating the at least one intermediate model object into executable source code; and generating an executable information extraction program from the executable source code. Other aspects are described and claimed.

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: One embodiment provides a method for generating an executable extraction program from a visual representation, the method including: utilizing at least one processor to execute computer code that performs the steps of: obtaining a validated model comprising a plurality of concepts, wherein each of the concepts comprises semantics associated with a visual representation of an object; generating at least one intermediate model object by parsing the validated model, wherein each of the intermediate model objects comprises a concept object; translating the at least one intermediate model object into executable source code; and generating an executable information extraction program from the executable source code. Other aspects are described and claimed.

Abstract: Embodiments of the present invention relate to a new method of entity integration using high-level scripting languages. In one embodiment, a method of and computer product for entity integration is provided. An entity declaration is read from a machine readable medium. The entity declaration describes an entity including at least one nested entity. An index declaration is read from a machine readable medium. The index declaration describes an index of nested entities. An entity population rule is read from a machine readable medium. The entity population rule describes a mapping from an input schema to an output schema. The output schema conforms to the entity declaration. A plurality of input records is read from a first data store. The input records conform to the input schema. The entity population rule applies to the plurality of records to create a plurality of output records complying with the output schema. An index of nested entities is populated. The index complies with the index declaration.

Abstract: Embodiments of the present invention relate to a new method of entity integration using high-level scripting languages. In one embodiment, a method of and computer product for entity integration is provided. An entity declaration is read from a machine readable medium. The entity declaration describes an entity including at least one nested entity. An index declaration is read from a machine readable medium. The index declaration describes an index of nested entities. An entity population rule is read from a machine readable medium. The entity population rule describes a mapping from an input schema to an output schema. The output schema conforms to the entity declaration. A plurality of input records is read from a first data store. The input records conform to the input schema. The entity population rule applies to the plurality of records to create a plurality of output records complying with the output schema. An index of nested entities is populated. The index complies with the index declaration.

Abstract: Data records are linked across a plurality of datasets. Each dataset contains at least one data record, and each data record is associated with an entity and includes one or more attributes of that entity and a value for each attribute. Values associated with attributes are compared across datasets, and matching attributes having values that satisfy a predetermined similarity threshold are identified. In addition, linkage points between pairs of datasets are identified. Each linkage point links one or more pairs of data records. Each data record in the pair of data records is contained in one of a given pair of datasets, and each pair of data records is associated with a common entity having matching attributes in the given pair of datasets. Data records associated with the common entities are linked across datasets using the identified linkage points.

Abstract: A method, system and program product for specifying, in a schema mapping framework, a mapping between a source schema and a target schema. The source and target schemas are schemas included in respective groups of registered, heterogeneous schemas. The source and target schemas may be of different types. Serialized versions of the source and target schemas include source objects and target objects, respectively. A mapping model is serialized into mapping objects that include logical references representing the source objects and logical references representing the target objects. The logical references are resolved to the source objects and target objects, thereby storing pointers to the source objects and to the target objects. After resolving the logical references, the mapping model includes the logical references and the pointers to the source and target objects.

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 method and system for specifying, in a schema mapping framework, a mapping between a source schema and a target schema. The source and target schemas are schemas included in respective groups of registered, heterogeneous schemas. The source and target schemas may be of different types. Serialized versions of the source and target schemas include source objects and target objects, respectively. A mapping model is serialized into mapping objects that include logical references representing the source objects and logical references representing the target objects. The logical references are resolved to the source objects and target objects, thereby storing pointers to the source objects and to the target objects. After resolving the logical references, the mapping model includes the logical references and the pointers to the source and target objects.

Abstract: A method and system for generating a query implementing a schema mapping. A mapping M is provided from a schema S to a schema T, where M relates S to T, and M includes a plurality of constraints. Schemas S and T each include one or more elements, and T includes at least one set type element. Mapping M is expressed in terms of at least one nested tuple-generating dependency. A query Q is generated where Q is capable of applying M to an input instance I to result in an output instance J, where I conforms to S, J conforms to T, and I and J satisfy the plurality of constraints. Instance J is in partitioned normal form (i.e., satisfies minimal union semantics) and includes no duplicate element instances.

Abstract: A method, system and program product for specifying, in a schema mapping framework, a mapping between a source schema and a target schema. The source and target schemas are schemas included in respective groups of registered, heterogeneous schemas. The source and target schemas may be of different types. Serialized versions of the source and target schemas include source objects and target objects, respectively. A mapping model is serialized into mapping objects that include logical references representing the source objects and logical references representing the target objects. The logical references are resolved to the source objects and target objects, thereby storing pointers to the source objects and to the target objects. After resolving the logical references, the mapping model includes the logical references and the pointers to the source and target objects.

Abstract: A method for generating nested mapping specifications and transformation queries based thereon. Basic mappings are generated based on source and target schemas and correspondences between elements of the schemas. A directed acyclic graph (DAG) is constructed whose edges represent ways in which each basic mapping is nestable under any of the other basic mappings. Any transitively implied edges are removed from the DAG. Root mappings of the DAG are identified. Trees of mappings are automatically extracted from the DAG, where each tree of mappings is rooted at a root mapping and expresses a nested mapping specification.

Abstract: A method and system for generating nested mapping specifications and transformation queries based thereon. Basic mappings are generated based on source and target schemas and correspondences between elements of the schemas. A directed acyclic graph (DAG) is constructed whose edges represent ways in which each basic mapping is nestable under any of the other basic mappings. Any transitively implied edges are removed from the DAG. Root mappings of the DAG are identified. Trees of mappings are automatically extracted from the DAG, where each tree of mappings is rooted at a root mapping and expresses a nested mapping specification. A transformation query is generated from the nested mapping specification by generating a first query for transforming source data into flat views of the target and a second query for nesting flat view data according to the target format. Generating the first query includes applying default Skolemization to the specification.

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: A system and method for generating a source schema-to-target schema mapping includes grouping user-defined value correspondences into potential sets such that, for each potential set, at most one value correspondence per target attribute exists. The value correspondences represent functions and filters for deriving values of target attributes from values of source attributes. Candidate sets are selected from the potential sets and then grouped into ranked covers. Using the best cover, an SQL query representing a source schema-to-target schema mapping is generated.

Abstract: The present system imports data from a source schema into a target schema while keeping the semantics, structure, and constraints of the data intact. The system is driven by user inputs that define a set of correspondences between the source schema and the target schema. The system meets the requirement that data produced at the target not violate the schema of the target; rather, the data must conform to the target schema. The system can be applied in both target materialization and query unfolding, producing all the meaningful queries required in data translation by finding all the associations that exist in the schemas. Each query maps from a source association to a target association. The user selects a subset of those queries that match the desired data translation. Target constraints are taken into account by the present system to infer the user intention and to guarantee that the generated data satisfies the structure and constraints of the target schema.