Abstract: Disclosed is an improved approach to represent RDF data in a database system, where one or more auxiliary tables are maintained for the RDF data. The auxiliary tables advantageously permit a database processing system to process a query using fewer numbers of joins or self-joins.

Abstract: Disclosed is an improved approach to represent RDF data in a database system, where one or more auxiliary tables are maintained for the RDF data. The auxiliary tables advantageously permit a database processing system to process a query using fewer numbers of joins or self-joins.

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 accessing a SPARQL endpoint that is specified from within a SQL database query language statement. A method embodiment receives a SQL database query language statement that is then parsed in order to identify the locations of one or more SPARQL endpoints to be accessed. The database query language statement comprises operations and/or queries (e.g., SPARQL queries) to be performed over at least some linked data (e.g., queries over named RDF graphs) found at the one or more SPARQL endpoints. The database query language statement can also specify relational operations such as a relational database table operation, and/or a view operation, and/or other relational database functions that operate in conjunction with retrieved linked data.

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: 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: A method, system, and computer program product for accessing a SPARQL endpoint that is specified from within a SQL database query language statement. A method embodiment receives a SQL database query language statement that is then parsed in order to identify the locations of one or more SPARQL endpoints to be accessed. The database query language statement comprises operations and/or queries (e.g., SPARQL queries) to be performed over at least some linked data (e.g., queries over named RDF graphs) found at the one or more SPARQL endpoints. The database query language statement can also specify relational operations such as a relational database table operation, and/or a view operation, and/or other relational database functions that operate in conjunction with retrieved linked data.