Interacting with Statistical Linked Data via OLAP Operations
نویسندگان
چکیده
Online Analytical Processing (OLAP) promises an interface to analyse Linked Data containing statistics going beyond other interaction paradigms such as follow-your-nose browsers, faceted-search interfaces and query builders. Transforming statistical Linked Data into a star schema to populate a relational database and applying a common OLAP engine do not allow to optimise OLAP queries on RDF or to directly propagate changes of Linked Data sources to clients. Therefore, as a new way to interact with statistics published as Linked Data, we investigate the problem of executing OLAP queries via SPARQL on an RDF store. First, we define projection, slice, dice and roll-up operations on single data cubes published as Linked Data reusing the RDF Data Cube vocabulary and show how a nested set of operations lead to an OLAP query. Second, we show how to transform an OLAP query to a SPARQL query which generates all required tuples from the data cube. In a small experiment, we show the applicability of our OLAP-to-SPARQL mapping in answering a business question in the financial domain.
منابع مشابه
Supporting Roll-Up and Drill-Down Operations over OLAP Data Cubes with Continuous Dimensions via Density-Based Hierarchical Clustering
In traditional OLAP systems, roll-up and drill-down operations over data cubes exploit fixed hierarchies defined on discrete attributes that play the roles of dimensions, and operate along them. However, in recent years, a new tendency of considering even continuous attributes as dimensions, hence hierarchical members become continuous accordingly, has emerged mostly due to novel and emerging a...
متن کاملA Metadata-based Recommender System for Statistical Linked Open Data
In recent years, there are increasing efforts of Business Intelligence (BI) and Semantic Web communities to enable On-Line Analytical Processing (OLAP) over Statistical Linked Open Data. Unlike internal sources where data organization is generally familiar, Linked Data sources are typically uncontrolled and bring challenges regarding the integrity constraints and data completeness required by t...
متن کاملSPARQL Benchmarking with Automatically Generated OLAP Queries
The growing use of data analytics on Linked Data requires SPARQL engines to efficiently execute Online Analytical Processing (OLAP) queries. While SPARQL 1.1 provides appropriate basic constructs, corresponding optimization of SPARQL engines is still in its infancy and further development lacks benchmarks that mimick the data distributions found in Link Data. In fact, existing work on OLAP benc...
متن کاملOLAP over Continuous Domains via Density-Based Hierarchical Clustering
In traditional OLAP systems, roll-up and drill-down operations over data cubes exploit fixed hierarchies defined on discrete attributes that play the roles of dimensions, and operate along them. However, in recent years, a new tendency of considering even continuous attributes as dimensions, hence hierarchical members become continuous accordingly, has emerged mostly due to novel and emerging a...
متن کاملModeling and Querying Data Cubes on the Semantic Web
The web is changing the way in which data warehouses are designed, used, and queried. With the advent of initiatives such as Open Data and Open Government, organizations want to share their multidimensional data cubes and make them available to be queried online. The RDF data cube vocabulary (QB), the W3C standard to publish statistical data in RDF, presents several limitations to fully support...
متن کامل