Abstract: Embodiments use successive refinement to allow a user to systematically explore the result set of an arbitrary query over RDF, such as a SPARQL query. A user inputs an arbitrary base query and modifies this query by replacing selected variables with values to which each selected variable is bound within the result set of the base query. Embodiments present, via a GUI, variable facets that may be substituted for query variables. Embodiments also present, through a GUI, a query history graph that represents query versions that a user has created. A user may navigate this query history graph to return to previously-created query versions. The GUI also provides information about the facets, including a number of results that would be included in the result set of the query version resulting from substitution of the facet for the associated variable.

Abstract: Embodiments use successive refinement to allow a user to systematically explore the result set of an arbitrary query over RDF, such as a SPARQL query. A user inputs an arbitrary base query and modifies this query by replacing selected variables with values to which each selected variable is bound within the result set of the base query. Embodiments present, via a GUI, variable facets that may be substituted for query variables. Embodiments also present, through a GUI, a query history graph that represents query versions that a user has created. A user may navigate this query history graph to return to previously-created query versions. The GUI also provides information about the facets, including a number of results that would be included in the result set of the query version resulting from substitution of the facet for the associated variable.

Abstract: Embodiments use successive refinement to allow a user to systematically explore the result set of an arbitrary query over RDF, such as a SPARQL query. A user inputs an arbitrary base query and modifies this query by replacing selected variables with values to which each selected variable is bound within the result set of the base query. Embodiments present, via a GUI, variable facets that may be substituted for query variables. Embodiments also present, through a GUI, a query history graph that represents query versions that a user has created. A user may navigate this query history graph to return to previously-created query versions. The GUI also provides information about the facets, including a number of results that would be included in the result set of the query version resulting from substitution of the facet for the associated variable.

Abstract: A method, system, and computer program product for transforming RDF quads to relational views. The method commences by receiving a named graph, the named graph comprising at least one RDF quad, and analyzing the named graph to produce analysis metadata. The method uses the analysis metadata to generate relational views. The method further comprises publishing a relational view in the form of a SPARQL query. The quality of the results can be quantitatively measured and reported by calculating a goodness score based at least in part on aspects of the relational view definitions. Several variants for transformation include generating relational view definitions formed using a named-graph strict variant, or a named-graph relaxed variant, or a named-graph agnostic variant. The transformations can form outputs responsive to characteristics or properties such as a number of classes, a number of single-valued properties, a number of nullability properties, or a number of type-uniformed ranges.

Abstract: A number of attributes of different attribute types, to be used to assign observation records of a data set to clusters, are identified. Attribute-type-specific distance metrics for the attributes, which can be combined to obtain a normalized aggregated distance of an observation record from a cluster representative, are selected. One or more iterations of a selected clustering methodology are implemented on the data set using resources of a machine learning service until targeted termination criteria are met. A given iteration includes assigning the observations to clusters of a current version of a clustering model based on the aggregated distances from the cluster representatives of the current version, and updating the cluster representatives to generate a new version of the clustering model.

Abstract: An approximate data structure to represent clusters of observation records of a data set is identified. A hierarchical representation of a plurality of clusters, including the targeted number of clusters among which the observation records are to be distributed, is generated. Each node of the hierarchy comprises an instance of the approximate data structure. Until a set of termination criteria are met, iterations of a selected clustering methodology are run. In a given iteration, distances of observation records from the cluster representatives of a current version of the model are computed using the hierarchical representation, and a new version of the model with modified cluster representatives is generated.

Abstract: A method, system, and computer program product for transforming RDF quads to relational views. The method commences by receiving a named graph, the named graph comprising at least one RDF quad, and analyzing the named graph to produce analysis metadata. The method uses the analysis metadata to generate relational views. The method further comprises publishing a relational view in the form of a SPARQL query. The quality of the results can be quantitatively measured and reported by calculating a goodness score based at least in part on aspects of the relational view definitions. Several variants for transformation include generating relational view definitions formed using a named-graph strict variant, or a named-graph relaxed variant, or a named-graph agnostic variant. The transformations can form outputs responsive to characteristics or properties such as a number of classes, a number of single-valued properties, a number of nullability properties, or a number of type-uniformed ranges.

Abstract: Systems and methods for visualizing relational data as RDF graphs in order to explore connections between data in the relational schema. The relational data is first converted into an initial RDF graph. Referential constraints between tables in the relational data, including unasserted referential constraints and pseudo-referential constraints, are automatically detected and used to augment the RDF graph. In addition, datatype properties in the RDF graph may be folded into annotation objects for better visualization. The resulting graph may be an edge-node graph, with edges corresponding to referential constraints between nodes corresponding to relational table rows.

Abstract: A method, system, and computer program product for transforming RDF quads to relational views. The method commences by receiving a named graph, the named graph comprising at least one RDF quad, and analyzing the named graph to produce analysis metadata. The method uses the analysis metadata to generate relational views. The method further comprises publishing a relational view in the form of a SPARQL query. The quality of the results can be quantitatively measured and reported by calculating a goodness score based at least in part on aspects of the relational view definitions. Several variants for transformation include generating relational view definitions formed using a named-graph strict variant, or a named-graph relaxed variant, or a named-graph agnostic variant. The transformations can form outputs responsive to characteristics or properties such as a number of classes, a number of single-valued properties, a number of nullability properties, or a number of type-uniformed ranges.

Abstract: Embodiments use successive refinement to allow a user to systematically explore the result set of an arbitrary query over RDF, such as a SPARQL query. A user inputs an arbitrary base query and modifies this query by replacing selected variables with values to which each selected variable is bound within the result set of the base query. Embodiments present, via a GUI, variable facets that may be substituted for query variables. Embodiments also present, through a GUI, a query history graph that represents query versions that a user has created. A user may navigate this query history graph to return to previously-created query versions. The GUI also provides information about the facets, including a number of results that would be included in the result set of the query version resulting from substitution of the facet for the associated variable.

Abstract: Systems and methods for visualizing relational data as RDF graphs in order to explore connections between data in the relational schema. The relational data is first converted into an initial RDF graph. Referential constraints between tables in the relational data, including unasserted referential constraints and pseudo-referential constraints, are automatically detected and used to augment the RDF graph. In addition, datatype properties in the RDF graph may be folded into annotation objects for better visualization. The resulting graph may be an edge-node graph, with edges corresponding to referential constraints between nodes corresponding to relational table rows.

Abstract: A method, system, and computer program product for normalized ranking of semantic query search results. The method commences by forming a SPARQL query, the SPARQL query specifying a collection of named RDF graphs, then executing the SPARQL query to retrieve matched documents selected from the collection of named RDF graphs. Having retrieved the matches, the method calculates an absolute normalized score for the matched document. The calculation of an absolute normalized score for a second matched document allows for relevance ranking. To enhance the relationship of the computer-calculated score to the relevance (and not solely to occurrence counts) embodiments consider the number of distinct variables selected in the SPARQL query, and also consider the total number of bindings to the aforementioned variables. For comparing from among possibly different sized documents, a further normalization component is implemented by considering the total number of triples found in the document's underlying subgraph.

Abstract: Disclosed is an approach for presenting RDF data as a set of relational views. By presenting the RDF data as relational views, this permits integrated access to the RDF-based data from existing relational database tools, such as by asserting SQL queries against the relational views. One or more classes are identified within the RDF data, wherein a relational view of the set of the relational views maps properties relating to a particular class.

Abstract: A method, system, and computer program product for transforming RDF quads to relational views. The method commences by receiving a named graph, the named graph comprising at least one RDF quad, and analyzing the named graph to produce analysis metadata. The method uses the analysis metadata to generate relational views. The method further comprises publishing a relational view in the form of a SPARQL query. The quality of the results can be quantitatively measured and reported by calculating a goodness score based at least in part on aspects of the relational view definitions. Several variants for transformation include generating relational view definitions formed using a named-graph strict variant, or a named-graph relaxed variant, or a named-graph agnostic variant. The transformations can form outputs responsive to characteristics or properties such as a number of classes, a number of single-valued properties, a number of nullability properties, or a number of type-uniformed ranges.

Abstract: The TABLE function mechanism available in a RDBMS is used to integrate RDF models into SQL queries. The table function invocation takes parameters including an RDF pattern, an RDF model, and an RDF rule base and returns result rows to the SQL query that contain RDF triples resulting from the application of the pattern to the triples of the model and the triples inferred by applying the rule base to the model. The RDBMS includes relational representations of the triples and the rules. Optimizations include indexes and materialized views of the representations of the triples, precomputed inferred triples, and a method associated with the TABLE function that rewrites the part of the SQL query that contains the TABLE function invocation as an equivalent SQL string. The latter technique is generally applicable to TABLE functions.

Abstract: A method, system, and computer program product for normalized ranking of semantic query search results. The method commences by forming a SPARQL query, the SPARQL query specifying a collection of named RDF graphs, then executing the SPARQL query to retrieve matched documents selected from the collection of named RDF graphs. Having retrieved the matches, the method calculates an absolute normalized score for the matched document. The calculation of an absolute normalized score for a second matched document allows for relevance ranking. To enhance the relationship of the computer-calculated score to the relevance (and not solely to occurrence counts) embodiments consider the number of distinct variables selected in the SPARQL query, and also consider the total number of bindings to the aforementioned variables. For comparing from among possibly different sized documents, a further normalization component is implemented by considering the total number of triples found in the document's underlying subgraph.

Abstract: An un-indexed, partitioned temporary table and an exchange table are used in the inferencing of semantic data in a relational database system. The exchange table has the same structure as a semantic data table storing the semantic data. In the inferencing process, a new partition is created in the semantic data table. Inference rules are executed on the semantic data table, and any newly inferred semantic data generated is added to the temporary table. Once no new data is generated, the inferred semantic data is copied from the temporary table into the exchange table. Indexes that are the same as indexes for the semantic data table are built for the exchange table. The indexed data in the exchange table is then exchanged into the new partition in the semantic data table. By use of the un-indexed, partitioned temporary table, incremental maintenance of indexes is avoided, thus allowing for greater efficiency.

Abstract: Disclosed is an approach for presenting RDF data as a set of relational views. By presenting the RDF data as relational views, this permits integrated access to the RDF-based data from relational tools.

Abstract: Techniques for using arbitrary sets of objects to constrain objects in database systems. The constraint set of objects is associated with the constrained object in the database system and the database system will perform an operation which adds an object to the constrained object only if the object being added belongs to the constraint set. In a preferred embodiment, the techniques are employed to obtain constraint sets of terms from ontologies which are then used to constrain columns containing those terms. An implementation of the techniques makes a materialized view out of the objects in the constraint set and uses the materialized view to define a referential integrity constraint on the constrained column.

Abstract: Techniques for generating hash values for instances of distinct data values. In the techniques, each distinct data value is mapped to hash value generation information which describes how to generate a unique hash value for instances of the distinct data value. The hash value generation information for a distinct data value is then used to generate the hash value for an instance of the distinct data value. The hash value generation information may indicate whether a collision has occurred in generating the hash values for instances of the distinct data values and if so, how the collision is to be resolved. The techniques are employed to normalize RDF triples by generating the UIDS employed in the normalization from the triples' lexical values.