Abstract: A system for storing graph data as a multi-dimensional cluster having a database with a graph dataset containing data and relationships between data pairs and a schema list of storage methods that use a table with columns and rows associated with data or relationships. An analyzer module to collect statistics of a graph dataset and a dimension identification module to identify a plurality of dimensions that each represent a column in the table. A schema creation and loading module creates a modified storage method and having a plurality of distinct table blocks and a plurality of table block indexes, one index for each table block and arranges the data and relationships in the given graph dataset in accordance with the modified storage method to create the multi-dimensional cluster.

Abstract: A system for identifying a schema for storing graph data includes a database containing a graph dataset of data and relationships between data pairs and a list of storage methods that each are a distinct structural arrangement of the data and relationships from the graph data set. An analyzer module collects statistics for the graph dataset, and a data classification module uses the collected statistics to calculate metrics describing the data and relationships in the graph dataset, uses the calculated metrics to group the data and relationships into a plurality of graph dataset subsets and. associates each graph dataset subset with one of the plurality of storage methods. The resulting group of storage methods associated with the plurality of graph dataset subsets includes a unique storage method for each graph dataset subset. The data and relationships in each graph dataset subset are arranged in accordance with associated storage methods.

Abstract: According to an aspect of the present principles, a method is provided for generating resource description framework benchmarks. The method includes deriving a resultant benchmark dataset with a user specified size and a user specified coherence from and with respect to an input dataset of a given size and a given coherence by determining which triples of subject-property-object to add to the input dataset or remove from the input dataset to derive the resultant benchmark dataset.

Abstract: Systems and methods for optimizing a query, and more particularly, systems and methods for finding optimal plans for graph queries by casting the task of finding the optimal plan as an integer programming (ILP) problem. A method for optimizing a query, comprises building a data structure for a query, the data structure including a plurality of components, wherein each of the plurality of components corresponds to at least one graph pattern, determining a plurality of flows of query variables between the plurality of components, and determining a combination of the plurality of flows between the plurality of components that results in a minimum cost to execute the query.

Abstract: A semantic query over an RDF database is received with RDF database statistics and access methods for evaluating triple patterns in the query. The semantic query is expressed as a parse tree containing triple patterns and logical relationships among the triple patterns. The parse tree and access methods create a data flow graph containing a plurality of triple pattern and access method pair nodes connected by a plurality of edges, and an optimal flow tree through the data flow graph is determined such that costs are minimized and all triple patterns in the semantic query are contained in the optimal flow tree. A structure independent execution tree defining a sequence of evaluation through the optimal flow tree is created and is transformed into a database structure dependent query plan. This is used to create an SQL query that is used to evaluate the semantic query over the RDF database.

Abstract: Multiquery optimization is performed in the context of RDF/SPARQL. Heuristic algorithms partition an input batch of queries into groups such that each group of queries can be optimized together. The optimization incorporates an efficient algorithm to discover the common sub-structures of multiple SPARQL queries and an effective cost model to compare candidate execution plans. No assumptions are made about the underlying SPARQL query engine. This provides portability across different RDF stores.

Abstract: Various embodiments virtualize data across heterogeneous formats. In one embodiment, a plurality of heterogeneous data sources is received as input. A local schema graph including a set of attribute nodes and a set of type nodes is generated for each of the plurality of heterogeneous data sources. A global schema graph is generated based on each local schema graph that has been generated. The global schema graph comprises each of the local schema graphs and at least one edge between at least one of two or more attributes nodes and two or more type nodes from different local schema graphs. The edge indicates a relationship between the data sources represented by the different local schema graphs comprising the two or more attributes nodes based on a computed similarity between at least one value associated with each of the two or more attributes nodes.

Abstract: A system for processing a transaction request. A transaction request is received by a server computer that includes a user identification and an associated request token, to execute on an application on the server computer. It is determined by the server computer whether available resources on the server computer to perform the transaction are below respective threshold values. In response to determining, by the server computer, that the available resources on the server computer to perform the transaction are below the threshold value, the server computer determines whether the user identification is allowed access to the application. In response to determining that the user identification is allowed access to the application, the transaction is executed on the server computer. In response to determining that the user identification is not allowed access to the application, the transaction is rejected.

Abstract: According to an aspect of the present principles, a method is provided for generating resource description framework benchmarks. The method includes deriving a resultant benchmark dataset with a user specified size and a user specified coherence from and with respect to an input dataset of a given size and a given coherence by determining which triples of subject-property-object to add to the input dataset or remove from the input dataset to derive the resultant benchmark dataset.

Abstract: A semantic query over an RDF database is received with RDF database statistics and access methods for evaluating triple patterns in the query. The semantic query is expressed as a parse tree containing triple patterns and logical relationships among the triple patterns. The parse tree and access methods create a data flow graph containing a plurality of triple pattern and access method pair nodes connected by a plurality of edges, and an optimal flow tree through the data flow graph is determined such that costs are minimized and all triple patterns in the semantic query are contained in the optimal flow tree. A structure independent execution tree defining a sequence of evaluation through the optimal flow tree is created and is transformed into a database structure dependent query plan. This is used to create an SQL query that is used to evaluate the semantic query over the RDF database.

Abstract: A schema for a dataset is identified by identifying a dataset comprising data and relationships between data pairs. An original schema is identified for the dataset. This original schema comprises an organizational structure. An initial fit between the dataset and the original schema is determined. The initial fit quantifying a conformity of the data in the dataset to the organizational structure of the original schema. A plurality of additional schemas are identified. Each additional schema is a distinct organizational schema. The dataset is partitioned into a plurality of subsets. Each subset comprises a modified fit quantifying a modified conformity of subset data in each subset to one of the original schema and the additional schemas. The modified fit is greater than the original fit.

Abstract: Techniques for indexing provenance data and evaluating provenance data queries are disclosed. For example, a method for processing one or more queries directed toward data associated with a data processing system comprises the following steps. One or more data items of a first data set associated with the data processing system are mapped to a first representation type and one or more data items of a second data set associated with the data processing system are mapped to a second representation type. A bi-directional index of a data provenance relation existing between the data items of the first data set and the data items of the second data set is computed. The bi-directional index is computed in terms of the first representation type and the second representation type. A query evaluation is performed using the bi-directional index, in response to receipt of a provenance query.

Abstract: Systems and methods for optimizing a query, and more particularly, systems and methods for finding optimal plans for graph queries by casting the task of finding the optimal plan as an integer programming (ILP) problem. A method for optimizing a query, comprises building a data structure for a query, the data structure including a plurality of components, wherein each of the plurality of components corresponds to at least one graph pattern, determining a plurality of flows of query variables between the plurality of components, and determining a combination of the plurality of flows between the plurality of components that results in a minimum cost to execute the query.

Abstract: A computer-implemented method, system, and article of manufacture for querying and integrating structured and unstructured data. The method includes: receiving entity information that is extracted from a first set of unstructured data using an open domain information extraction system, wherein the entity in-formation comprises relationship information between a first entity and a second entity of the first set of unstructured data; recognizing a pattern based on the relationship information and creating a schema for the first set of unstructured data based on the pattern; and associating an element of the created schema with (i) an entity of a second set of unstructured data or (ii) a schema element of an existing set of structured data if there is sufficient overall similarity between the created schema element and either the second unstructured data entity or the schema element of the existing structured data.

Abstract: A semantic query over an RDF database is received with RDF database statistics and access methods for evaluating triple patterns in the query. The semantic query is expressed as a parse tree containing triple patterns and logical relationships among the triple patterns. The parse tree and access methods create a data flow graph containing a plurality of triple pattern and access method pair nodes connected by a plurality of edges, and an optimal flow tree through the data flow graph is determined such that costs are minimized and all triple patterns in the semantic query are contained in the optimal flow tree. A structure independent execution tree defining a sequence of evaluation through the optimal flow tree is created and is transformed into a database structure dependent query plan. This is used to create an SQL query that is used to evaluate the semantic query over the RDF database.

Abstract: Keyword searching is used to explore and search large Resource Description Framework datasets having unknown or constantly changing structures. A succinct and effective summarization is built from the underlying resource description framework data. Given a keyword query, the summarization lends significant pruning powers to exploratory keyword searches and leads to much better efficiency compared to previous work. The summarization returns exact results and can be updated incrementally and efficiently.

Abstract: A method of performing a graph query issued by a user is provided. The method includes performing on a processor, receiving a user graph query. The method includes rewriting the user graph query as a new query based on a query policy expressed in a graph query language. The method includes performing the new query on graph data to obtain a result.

Abstract: Keyword searching is used to explore and search large Resource Description Framework datasets having unknown or constantly changing structures. A succinct and effective summarization is built from the underlying resource description framework data. Given a keyword query, the summarization lends significant pruning powers to exploratory keyword searches and leads to much better efficiency compared to previous work. The summarization returns exact results and can be updated incrementally and efficiently.

Abstract: A system for storing graph data as a multi-dimensional cluster having a database with a graph dataset containing data and relationships between data pairs and a schema list of storage methods that use a table with columns and rows associated with data or relationships. An analyzer module to collect statistics of a graph dataset and a dimension identification module to identify a plurality of dimensions that each represent a column in the table. A schema creation and loading module creates a modified storage method and having a plurality of distinct table blocks and a plurality of table block indexes, one index for each table block and arranges the data and relationships in the given graph dataset in accordance with the modified storage method to create the multi-dimensional cluster.

Abstract: A system for identifying a schema for storing graph data includes a database containing a graph dataset of data and relationships between data pairs and a list of storage methods that each are a distinct structural arrangement of the data and relationships from the graph data set. An analyzer module collects statistics for the graph dataset, and a data classification module uses the collected statistics to calculate metrics describing the data and relationships in the graph dataset, uses the calculated metrics to group the data and relationships into a plurality of graph dataset subsets and. associates each graph dataset subset with one of the plurality of storage methods. The resulting group of storage methods associated with the plurality of graph dataset subsets includes a unique storage method for each graph dataset subset. The data and relationships in each graph dataset subset are arranged in accordance with associated storage methods.