CiDHouse: Contextual SemantIc Data WareHouses

  • Selma Khouri
  • Lama El Saraj
  • Ladjel Bellatreche
  • Bernard Espinasse
  • Nabila Berkani
  • Sophie Rodier
  • Thérèse Libourel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8056)

Abstract

Dealing with contextualized data is a key challenge in data warehouses (\(\mathcal{D}\mathcal{W}\)). Nowadays, \(\mathcal{D}\mathcal{W}\) systems are often monocontext. However, in real life applications, \(\mathcal{D}\mathcal{W}\) indicators are shared by many users with different profiles. In this paper, we propose an ontology-based approach for designing multi-contextual \(\mathcal{D}\mathcal{W}\). An ontology formalism incorporating the contextualization concepts is given. We propose to consider the contextualization at the conceptual level. We validate our proposal using a real case study from the medical domain.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bellatreche, L., Khouri, S., Berkani, N.: Semantic data warehouse design: From ETL to deployment à la carte. In: Meng, W., Feng, L., Bressan, S., Winiwarter, W., Song, W. (eds.) DASFAA 2013, Part II. LNCS, vol. 7826, pp. 64–83. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  2. 2.
    Brockmans, S., Haase, P., Serafini, L., Stuckenschmidt, H.: Formal and conceptual comparison of ontology mapping languages. In: Stuckenschmidt, H., Parent, C., Spaccapietra, S. (eds.) Modular Ontologies. LNCS, vol. 5445, pp. 267–291. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  3. 3.
    Gali, A., Chen, C., Claypool, K., Uceda-Sosa, R.: From ontology to relational databases. In: ER Workshops, pp. 278–289 (2004)Google Scholar
  4. 4.
    Garrigós, I., Pardillo, J., Mazón, J.-N., Trujillo, J.: A conceptual modeling approach for OLAP personalization. In: Laender, A.H.F., Castano, S., Dayal, U., Casati, F., de Oliveira, J.P.M. (eds.) ER 2009. LNCS, vol. 5829, pp. 401–414. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  5. 5.
    Pérez, J.M., Berlanga, R., Aramburu, M.J., Pedersen, T.B.: A relevance-extended multi-dimensional model for a data warehouse contextualized with documents. In: DOLAP 2005 (2005)Google Scholar
  6. 6.
    Pierra, G.: Context representation in domain ontologies and its use for semantic integration of data. Journal of Data Semantics (JoDS) 10, 174–211 (2008)Google Scholar
  7. 7.
    Pitarch, Y., Favre, C., Laurent, A., Poncelet, P.: Enhancing flexibility and expressivity of contextual hierarchies. In: Fuzzy Systems, pp. 1–8 (2012)Google Scholar
  8. 8.
    Skoutas, D., Simitsis, A.: Ontology-based conceptual design of ETL processes for both structured and semi-structured data. IJSWIS 3(4), 1–24 (2007)Google Scholar
  9. 9.
    Stefanidis, K., Shabib, N., Nørvåg, K., Krogstie, J.: Contextual recommendations for groups. In: Advances in Conceptual Modeling, pp. 89–97 (2012)Google Scholar
  10. 10.
    Wache, H., Vogele, T., Visser, U., Stuckenschmidtet, H., et al.: Ontology-based integration of information - a survey of existing approaches. In: OIS, pp. 108–117 (2001)Google Scholar
  11. 11.
    Wang, X.H., Zhang, D.Q., Gu, T., Pung, H.K.: Ontology based context modeling and reasoning using owl. In: PERCOMW, pp. 18–22 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Selma Khouri
    • 1
    • 3
  • Lama El Saraj
    • 2
    • 4
  • Ladjel Bellatreche
    • 3
  • Bernard Espinasse
    • 2
  • Nabila Berkani
    • 1
  • Sophie Rodier
    • 4
  • Thérèse Libourel
    • 5
  1. 1.ESIAlgiersAlgeria
  2. 2.LSISMarseilleFrance
  3. 3.LIAS/ISAE-ENSMAFuturoscopeFrance
  4. 4.Assistance publique des Hôpitaux de MarseilleFrance
  5. 5.LIRMMMontpellierFrance

Personalised recommendations