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dc.contributor.authorVarga, Jovan
dc.contributor.authorRomero Moral, Óscar
dc.contributor.authorBach Pedersen, Torben
dc.contributor.authorThomsen, Christian
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació
dc.date.accessioned2018-11-15T13:03:06Z
dc.date.available2020-06-19T00:26:18Z
dc.date.issued2018-10
dc.identifier.citationVarga, J., Romero, O., Bach, T., Thomsen, C. Analytical metadata modeling for next generation BI systems. "Journal of systems and software", Octubre 2018, vol. 144, p. 240-254.
dc.identifier.issn0164-1212
dc.identifier.urihttp://hdl.handle.net/2117/124373
dc.description.abstractBusiness Intelligence (BI) systems are extensively used as in-house solutions to support decision-making in organizations. Next generation BI 2.0 systems claim for expanding the use of BI solutions to external data sources and assisting the user in conducting data analysis. In this context, the Analytical Metadata (AM) framework defines the metadata artifacts (e.g., schema and queries) that are exploited for user assistance purposes. As such artifacts are typically handled in ad-hoc and system specific manners, BI 2.0 argues for a flexible solution supporting metadata exploration across different systems. In this paper, we focus on the AM modeling. We propose SM4AM, an RDF-based Semantic Metamodel for AM. On the one hand, we claim for ontological metamodeling as the proper solution, instead of a fixed universal model, due to (meta)data models heterogeneity in BI 2.0. On the other hand, RDF provides means for facilitating defining and sharing flexible metadata representations. Furthermore, we provide a method to instantiate our metamodel. Finally, we present a real-world case study and discuss how SM4AM, specially the schema and query artifacts, can help traversing different models instantiating our metamodel and enabling innovative means to explore external repositories in what we call metamodel-driven (meta)data exploration.
dc.format.extent15 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Sistemes d'informació
dc.subject.lcshMetadata
dc.subject.lcshDecision support systems
dc.subject.otherBusiness intelligence
dc.subject.otherOntological metamodeling
dc.titleAnalytical metadata modeling for next generation BI systems
dc.typeArticle
dc.subject.lemacMetadades
dc.subject.lemacSistemes d'ajuda a la decisió
dc.contributor.groupUniversitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering
dc.contributor.groupUniversitat Politècnica de Catalunya. IMP - Information Modeling and Processing
dc.identifier.doi10.1016/j.jss.2018.06.039
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0164121218301274
dc.rights.accessOpen Access
local.identifier.drac23504509
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/V PRI 2010-2013/2014 SGR 1534
local.citation.authorVarga, J.; Romero, O.; Bach, T.; Thomsen, C.
local.citation.publicationNameJournal of systems and software
local.citation.volume144
local.citation.startingPage240
local.citation.endingPage254


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Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain