Ir al contenido (pulsa Retorno)

Universitat Politècnica de Catalunya

    • Català
    • Castellano
    • English
    • LoginRegisterLog in (no UPC users)
  • mailContact Us
  • world English 
    • Català
    • Castellano
    • English
  • userLogin   
      LoginRegisterLog in (no UPC users)

UPCommons. Global access to UPC knowledge

Banner header
60.707 UPC E-Prints
You are here:
View Item 
  •   DSpace Home
  • E-prints
  • Grups de recerca
  • inSSIDE - integrated Software, Service, Information and Data Engineering
  • Articles de revista
  • View Item
  •   DSpace Home
  • E-prints
  • Grups de recerca
  • inSSIDE - integrated Software, Service, Information and Data Engineering
  • Articles de revista
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Analytical metadata modeling for next generation BI systems

Thumbnail
View/Open
jss2018.pdf (1,991Mb)
Share:
 
 
10.1016/j.jss.2018.06.039
 
  View Usage Statistics
Cita com:
hdl:2117/124373

Show full item record
Varga, JovanMés informació
Romero Moral, ÓscarMés informacióMés informacióMés informació
Bach Pedersen, Torben
Thomsen, Christian
Document typeArticle
Defense date2018-10
Rights accessOpen Access
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
Abstract
Business 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.
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. 
URIhttp://hdl.handle.net/2117/124373
DOI10.1016/j.jss.2018.06.039
ISSN0164-1212
Publisher versionhttps://www.sciencedirect.com/science/article/pii/S0164121218301274
Collections
  • inSSIDE - integrated Software, Service, Information and Data Engineering - Articles de revista [113]
  • Departament d'Enginyeria de Serveis i Sistemes d'Informació - Articles de revista [203]
  • GESSI - Grup d'Enginyeria del Software i dels Serveis - Articles de revista [56]
  • IMP - Information Modeling and Processing - Articles de revista [109]
Share:
 
  View Usage Statistics

Show full item record

FilesDescriptionSizeFormatView
jss2018.pdf1,991MbPDFView/Open

Browse

This CollectionBy Issue DateAuthorsOther contributionsTitlesSubjectsThis repositoryCommunities & CollectionsBy Issue DateAuthorsOther contributionsTitlesSubjects

© UPC Obrir en finestra nova . Servei de Biblioteques, Publicacions i Arxius

info.biblioteques@upc.edu

  • About This Repository
  • Contact Us
  • Send Feedback
  • Privacy Settings
  • Inici de la pàgina