Skip to main content

CiDHouse: Contextual SemantIc Data WareHouses

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,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.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  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)

    Chapter  Google Scholar 

  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)

    Chapter  Google Scholar 

  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. 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)

    Chapter  Google Scholar 

  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. 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. 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. 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. Stefanidis, K., Shabib, N., Nørvåg, K., Krogstie, J.: Contextual recommendations for groups. In: Advances in Conceptual Modeling, pp. 89–97 (2012)

    Google Scholar 

  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. 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 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Khouri, S. et al. (2013). CiDHouse: Contextual SemantIc Data WareHouses. In: Decker, H., Lhotská, L., Link, S., Basl, J., Tjoa, A.M. (eds) Database and Expert Systems Applications. DEXA 2013. Lecture Notes in Computer Science, vol 8056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40173-2_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40173-2_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40172-5

  • Online ISBN: 978-3-642-40173-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics