Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/26228
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dc.contributor.authorGomez, Leticia-
dc.contributor.authorKUIJPERS, Bart-
dc.contributor.authorVAISMAN, Alejandro-
dc.date.accessioned2018-06-28T13:40:38Z-
dc.date.available2018-06-28T13:40:38Z-
dc.date.issued2017-
dc.identifier.citationChatziantoniou, Damianos; Castellanos, Malu; Chrysanthis, Panos K. (Ed.). Proceedings of the eleventh international workshop on real-time business intelligence and analytics, Assoc computing machinery,p. 1-8 (Art N° 6)-
dc.identifier.isbn9781450354257-
dc.identifier.urihttp://hdl.handle.net/1942/26228-
dc.description.abstractIn current Big Data scenarios, traditional data warehousing and Online Analytical Processing (OLAP) operations on cubes are clearly not sufficient to address the current data analysis requirements. Nevertheless, OLAP operations and models can expand the possibilities of graph analysis beyond the traditional graph-based computation. In spite of this, there is not much work on the problem of taking OLAP analysis to the graph data model. In previous work we proposed a multidimensional (MD) data model for graph analysis, that considers not only the basic graph data, but background information in the form of dimension hierarchies as well. The graphs in our model are node-and edge-labelled directed multi-hypergraphs, called graphoids, defined at several different levels of granularity. In this paper we show how we implemented this proposal over the widely used Neo4J graph database, discuss implementation issues, and present a detailed case study to show how OLAP operations can be used on graphs.-
dc.description.sponsorshipAlejandro Vaisman was supported by a travel grant from Hasselt University (Korte verblijven-inkomende mobiliteit, BOF16KV09), and by the PICT-0787-2014 project.-
dc.language.isoen-
dc.publisherAssoc computing machinery-
dc.relation.ispartofseriesACM International Conference Proceeding Series-
dc.rightsPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. BIRTE ’17, August 28, 2017, Munich, Germany © 2017 Association for Computing Machinery.-
dc.subject.otherOLAP; graph databases-
dc.titlePerforming OLAP over Graph Data: Query Language, Implementation, and a Case Study-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsChatziantoniou, Damianos-
local.bibliographicCitation.authorsCastellanos, Malu-
local.bibliographicCitation.authorsChrysanthis, Panos K.-
local.bibliographicCitation.conferencedate28/08/2017-
local.bibliographicCitation.conferencename11th International Workshop on Real-Time Business Intelligence and Analytics (BIRTE)-
local.bibliographicCitation.conferenceplaceMunich, Germany-
dc.identifier.epage8-
dc.identifier.spage1-
local.bibliographicCitation.jcatC1-
dc.description.notesGomez, L (reprint author), Inst Tecnol Buenos Aires, Buenos Aires, DF, Argentina, lgomez@itba.edu.ar; bart.kuijpers@uhasselt.be; avaisman@itba.edu.ar-
local.publisher.placeNew York, NY, USA-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
local.bibliographicCitation.artnr6-
dc.identifier.doi10.1145/3129292.3129293-
dc.identifier.isi000426583400006-
local.bibliographicCitation.btitleProceedings of the eleventh international workshop on real-time business intelligence and analytics-
item.validationecoom 2019-
item.contributorGomez, Leticia-
item.contributorKUIJPERS, Bart-
item.contributorVAISMAN, Alejandro-
item.accessRightsOpen Access-
item.fullcitationGomez, Leticia; KUIJPERS, Bart & VAISMAN, Alejandro (2017) Performing OLAP over Graph Data: Query Language, Implementation, and a Case Study. In: Chatziantoniou, Damianos; Castellanos, Malu; Chrysanthis, Panos K. (Ed.). Proceedings of the eleventh international workshop on real-time business intelligence and analytics, Assoc computing machinery,p. 1-8 (Art N° 6).-
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