Mostra el registre d'ítem simple
QB2OLAP : enabling OLAP on statistical linked open data
dc.contributor.author | Varga, Jovan |
dc.contributor.author | Etcheverry, Lorena |
dc.contributor.author | Vaisman, Alejandro |
dc.contributor.author | Romero Moral, Óscar |
dc.contributor.author | Bach Pedersen, Torben |
dc.contributor.author | Thomsen, Christian |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació |
dc.date.accessioned | 2017-01-12T09:15:12Z |
dc.date.available | 2017-01-12T09:15:12Z |
dc.date.issued | 2016 |
dc.identifier.citation | Varga, J., Etcheverry, L., Vaisman, A., Romero, O., Bach, T., Thomsen, C. QB2OLAP : enabling OLAP on statistical linked open data. A: IEEE International Conference on Data Engineering. "2016 IEEE 32nd International Conference on Data Engineering (ICDE). Proceedings". Helsinki: 2016, p. 1346-1349. |
dc.identifier.isbn | 978-1-5090-2020-1 |
dc.identifier.uri | http://hdl.handle.net/2117/99074 |
dc.description.abstract | Publication and sharing of multidimensional (MD) data on the Semantic Web (SW) opens new opportunities for the use of On-Line Analytical Processing (OLAP). The RDF Data Cube (QB) vocabulary, the current standard for statistical data publishing, however, lacks key MD concepts such as dimension hierarchies and aggregate functions. QB4OLAP was proposed to remedy this. However, QB4OLAP requires extensive manual annotation and users must still write queries in SPARQL, the standard query language for RDF, which typical OLAP users are not familiar with. In this demo, we present QB2OLAP, a tool for enabling OLAP on existing QB data. Without requiring any RDF, QB(4OLAP), or SPARQL skills, it allows semi-automatic transformation of a QB data set into a QB4OLAP one via enrichment with QB4OLAP semantics, exploration of the enriched schema, and querying with the high-level OLAP language QL that exploits the QB4OLAP semantics and is automatically translated to SPARQL. |
dc.format.extent | 4 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació |
dc.subject.lcsh | Data mining |
dc.subject.other | data mining |
dc.subject.other | data warehouses |
dc.subject.other | query languages |
dc.subject.other | semantic Web |
dc.subject.other | on-line analytical processing |
dc.subject.other | RDF Data Cube vocabulary |
dc.subject.other | query language |
dc.subject.other | data warehousing |
dc.subject.other | DW |
dc.title | QB2OLAP : enabling OLAP on statistical linked open data |
dc.type | Conference report |
dc.subject.lemac | Mineria de dades |
dc.contributor.group | Universitat Politècnica de Catalunya. MPI - Modelització i Processament de la Informació |
dc.identifier.doi | 10.1109/ICDE.2016.7498341 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7498341 |
dc.rights.access | Open Access |
local.identifier.drac | 18785464 |
dc.description.version | Postprint (author's final draft) |
local.citation.author | Varga, J.; Etcheverry, L.; Vaisman, A.; Romero, O.; Bach, T.; Thomsen, C. |
local.citation.contributor | IEEE International Conference on Data Engineering |
local.citation.pubplace | Helsinki |
local.citation.publicationName | 2016 IEEE 32nd International Conference on Data Engineering (ICDE). Proceedings |
local.citation.startingPage | 1346 |
local.citation.endingPage | 1349 |