Abstract: Lineage graphs corresponding to data objects are generated. A data object of the data objects is associated with a source dataset table stored at a data lineage server (DLS). The source dataset table includes data of the data object received from a dataset stored at a data source system (DSS). A lineage graph corresponding to the dataset is determined from the lineage graphs. Based on the lineage graph, one or more data lineage structures are provided. The one or more data lineage structures include data from the dataset and from one or more datasets related to the dataset, and define lineage relationships between the data object and one or more data objects corresponding to the one or more datasets.

Abstract: Lineage graphs corresponding to data objects are generated. A data object of the data objects is associated with a source dataset table stored at a data lineage server (DLS). The source dataset table includes data of the data object received from a dataset stored at a data source system (DSS). A lineage graph corresponding to the dataset is determined from the lineage graphs. Based on the lineage graph, one or more data lineage structures are provided. The one or more data lineage structures include data from the dataset and from one or more datasets related to the dataset, and define lineage relationships between the data object and one or more data objects corresponding to the one or more datasets.

Abstract: Apparatus, systems, and methods may operate to receive an original query plan, to transform the original query plan into an equivalent executable compact query plan, and to store the compact query plan on a machine readable device. Further activities may include computing maximal source sub-queries associated with the compact query plan, and computing semi-join reductions of the maximal source sub-queries to provide an executable derivative query plan, which may also be stored on a machine readable device. Additional apparatus, systems, and methods are disclosed.

Abstract: Apparatus, systems, and methods may operate to receive an original query plan, to transform the original query plan into an equivalent executable compact query plan, and to store the compact query plan on a machine readable device. Further activities may include computing maximal source sub-queries associated with the compact query plan, and computing semi-join reductions of the maximal source sub-queries to provide an executable derivative query plan, which may also be stored on a machine readable device. Additional apparatus, systems, and methods are described.

Abstract: Apparatus, systems, and methods may operate to receive an original query plan, to transform the original query plan into an equivalent executable compact query plan, and to store the compact query plan on a machine readable device. Further activities may include computing maximal source sub-queries associated with the compact query plan, and computing semi-join reductions of the maximal source sub-queries to provide an executable derivative query plan, which may also be stored on a machine readable device. Additional apparatus, systems, and methods are disclosed.

Abstract: A computer readable medium includes executable instructions to define an individual publication schema for each heterogeneous source of a set of heterogeneous sources. Each individual publication schema specifies mapping rules between data from a heterogeneous source and a non-permanent structured instance of data. A non-permanent structured instance of data as defined by an individual publication schema is generated. An integration schema defining a set of integration rules for combining data from each non-permanent structured instance of data as defined by individual publication schema is established. A target non-permanent structured instance of data to include data from the plurality of heterogeneous sources based on at least one integration schema is formed.

Abstract: Apparatus, systems, and methods may operate to receive an original query plan, to transform the original query plan into an equivalent executable compact query plan, and to store the compact query plan on a machine readable device. Further activities may include computing maximal source sub-queries associated with the compact query plan, and computing semi-join reductions of the maximal source sub-queries to provide an executable derivative query plan, which may also be stored on a machine readable device. Additional apparatus, systems, and methods are disclosed.

Abstract: A computer readable medium includes executable instructions to define an individual publication schema for each heterogeneous source of a set of heterogeneous sources. Each individual publication schema specifies mapping rules between data from a heterogeneous source and a non-permanent structured instance of data. A non-permanent structured instance of data as defined by an individual publication schema is generated. An integration schema defining a set of integration rules for combining data from each non-permanent structured instance of data as defined by individual publication schema is established. A target non-permanent structured instance of data to include data from the plurality of heterogeneous sources based on at least one integration schema is formed.

Abstract: A computer readable storage medium includes executable instructions to derive a table representing operations associated with an application. One or more parameters are received. A query is executed against the table if the parameters are resolvable with respect to one or more columns in the table. A derived query is constructed based on one or more additional parameters if the parameters are not resolvable with respect to one or more columns in the table. The derived query is executed against the table. A query result is returned.

Abstract: The invention includes a computer readable storage medium with executable instructions to translate a data source into a set of data elements, where a data element in the set of data elements includes a set of data properties. The set of data elements is displayed using a visualization. A group of data elements selected from the set of data elements is received. A group of data properties selected from the set of data properties associated with each data element in the group of data elements is received. A table schema for data elements in the group of data elements is provided. The group of data elements is converted into a target data source.

Abstract: An object-focused workflow system for processing a received object in accordance with a declarative workflow specification. The specification includes modules and attributes, where module execution results in the evaluation of attributes, and may include the initiation of a side-effect action performed by an external component. Whether modules are to be executed for a particular received object is determined by associated enabling conditions. Attributes may be evaluated in accordance with computation rules and a combining policy, where the computation rules specify how values are to be contributed to an attribute, and the combining policy indicates how those contributed values are combined in order to assign a value to the attribute. Tasks in the workflow system may be executed eagerly in order to improve the performance of the workflow system.

Abstract: A computer readable medium includes executable instructions to define an individual publication schema for each heterogeneous source of a set of heterogeneous sources. Each individual publication schema specifies mapping rules between data from a heterogeneous source and a non-permanent structured instance of data. A non-permanent structured instance of data as defined by an individual publication schema is generated. An integration schema defining a set of integration rules for combining data from each non-permanent structured instance of data as defined by individual publication schema is established. A target non-permanent structured instance of data to include data from the plurality of heterogeneous sources based on at least one integration schema is formed.

Abstract: A graphical user interface (GUI) is provided for use in conjunction with attribute evaluation utilizing computation rules and a combining policy. The graphical user interface displays a visual representation of the evaluation of attributes. The GUI displays a representation of the evaluation status of attributes and their associated computation rules during execution. The display may be updated dynamically to provide a user with a visual representation of the progression of attribute evaluation. The representation of evaluation status may include representations of the values assigned to, as well as the state of, data items and associated computation rules. States may be visually represented in the display in various ways, such as using various colors or labels associated with the data items and associated computation rules. Further, the particular data items and computation rules for which evaluation status is represented may be user selectable.

Abstract: A graphical user interface (GUI) is provided for use in conjunction with attribute evaluation utilizing computation rules and a combining policy. The graphical user interface displays a visual representation of the evaluation of attributes. The GUI displays a representation of the evaluation status of attributes and their associated computation rules during execution. The display may be updated dynamically to provide a user with a visual representation of the progression of attribute evaluation. The representation of evaluation status may include representations of the values assigned to, as well as the state of, data items and associated computation rules. States may be visually represented in the display in various ways, such as using various colors or labels associated with the data items and associated computation rules. Further, the particular data items and computation rules for which evaluation status is represented may be user selectable.

Abstract: An object-focused workflow system for processing a received object in accordance with a declarative workflow specification. The specification includes modules and attributes, where module execution results in the evaluation of attributes, and may include the initiation of a side-effect action performed by an external component. Whether modules are to be executed for a particular received object is determined by associated enabling conditions. Attributes may be evaluated in accordance with computation rules and a combining policy, where the computation rules specify how values are to be contributed to an attribute, and the combining policy indicates how those contributed values are combined in order to assign a value to the attribute. Tasks in the workflow system may be executed eagerly in order to improve the performance of the workflow system.