Abstract
Data warehouses (DW) and OLAP systems are technologies allowing the on-line analysis of huge volume of data according to decision-makers’ needs. Designing DW involves taking into account functional requirements and data sources (mixed design methodology) [1]. But, for complex applications, existing automatic design methodologies seem inefficient. In some cases, decision-makers need querying, as a dimension, data which have been defined as facts by actual automatic mixed approachs. Therefore, in this paper, we offer a new mixed refinement methodology relevant to constellation multidimensional schema. The proposed methodolgy allows to decision-makers to enrich a dimension with factual data. In order to validate our theoretical proposals, we have implemented an enrichment tool and we have tested it on a real case study from bird biodiversity.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
In this paper, the notation \((f_{i},d_{j})\) represents the arc from fact node \(f_{i}\) to dimensional node \(d_{j}\).
- 2.
‘*’ means ‘all members of the dimension’.
- 3.
- 4.
- 5.
- 6.
- 7.
References
Phipps, C., Davis, K.C.: Automating data warehouse conceptual schema design and evaluation. In: Proceedings of the 4th International Workshop on Design and Management of Data Warehouses (DMDW), vol. 2 (2002)
Kimball, R.: The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses. Wiley, New York (1996)
Romero, O., Abello, A.: A survey of multidimensional modeling methodologies. Int. J. Data Warehouse. Min. 5, 1–23 (2009)
Mahboubi, H., Ralaivao, J.C., Loudcher, S., Boussaïd, O., Bentayeb, F., Darmont, J., et al.: X-WACoDa: an XML-based approach for warehousing and analyzing complex data. In: Data Warehousing Design and Advanced Engineering Applications: Methods for Complex Construction, pp. 38–54 (2009)
Jensen, M.R., Holmgren, T., Pedersen, T.B.: Discovering multidimensional structure in relational data. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds.) DaWaK 2004. LNCS, vol. 3181, pp. 138–148. Springer, Heidelberg (2004)
Favre, C., Bentayeb, F., Boussaid, O.: A knowledge-driven data warehouse model for analysis evolution. Frontiers Artif. Intell. Appl. 143, 271 (2006)
Sautot, L., Faivre, B., Journaux, L., Molin, P.: The hierarchical agglomerative clustering with gower index: a methodology for automatic design of OLAP cube in ecological data processing context. Ecol. Inf. 26, 217–230 (2014) (in Press)
Jovanovic, P., Romero, O., Simitsis, A., Abelló, A.: Ore: An iterative approach to the design and evolution of multi-dimensional schemas. In: Proceedings of the Fifteenth International Workshop on Data Warehousing and OLAP, DOLAP 2012, pp. 1–8. ACM, New York (2012)
Romero, O., Abello, A.: Automatic validation of requirements to support multidimensional design. Data Knowl. Eng. 69, 917–942 (2010)
Carmè, A., Mazon, J.N., Rizzi, S.: A model-driven heuristic approach for detecting multidimensional facts in relational data sources. In: Bach Pedersen, T., Mohania, M.K., Tjoa, A.M. (eds.) DAWAK 2010. LNCS, vol. 6263, pp. 13–24. Springer, Heidelberg (2010)
Nguyen, T.B., Tjoa, A.M., Wagner, R.R.: An object oriented multidimensional data model for OLAP. In: Lu, H., Zhou, A. (eds.) WAIM 2000. LNCS, vol. 1846, pp. 69–82. Springer, Heidelberg (2000)
Messaoud, R.B., Boussaid, O., Rabaséda, S.: A new OLAP aggregation based on the AHC technique. In: DOLAP 2004, ACM Seventh International Workshop on Data Warehousing and OLAP, pp. 65–72 (2004)
Bentayeb, F.: K-means based approach for OLAP dimension updates. In: 10th International Conference on Enterprise Information Systems (ICEIS), pp. 531–534 (2008)
Leonhardi, B., Mitschang, B., Pulido, R., Sieb, C., Wurst, M.: Augmenting OLAP exploration with dynamic advanced analytics. In: 13th International Conference on Extending Database Technology (EDBT 2010) (2010)
Ceci, M., Cuzzocrea, A., Malerba, D.: OLAP over continuous domains via density-based hierarchical clustering. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds.) KES 2011, Part II. LNCS, vol. 6882, pp. 559–570. Springer, Heidelberg (2011)
Sautot, L., Bimonte, S., Journaux, L., Faivre, B.: A methodology and tool for rapid prototyping of data warehouses using data mining: application to birds biodiversity. In: Ait Ameur, Y., Bellatreche, L., Papadopoulos, G.A. (eds.) MEDI 2014. LNCS, vol. 8748, pp. 250–257. Springer, Heidelberg (2014)
Arora, M., Gosain, A.: Schema evolution for data warehouse: a survey. Int. J. Comput. Appl. (0975–8887) 22, 6–14 (2011)
Subotic, D., Poscic, P., Jovanovic, V.: Data warehouse schema evolution: state of the art. In: Proceedings of the Central European Conference on Information and Intelligent Systems, pp. 18–25 (2014)
Legube, B., Merlet, N.: Les indicateurs biologiques de la qualité de l’eau. In: L’analyse de l’eau. 9e edn., pp. 865–962. Dunod (2009)
Blondel, J., Ferry, C., Frochot, B.: Point counts with unlimited distance. In: Ralph, C.J., Scott, J.M. (eds.) Estimating Numbers of Terrestrial Birds. Studies in Avian Biology. vol. 6, pp. 414–420 (1981)
I.B.C.C.: Censuring breeding bird by the I.P.A. method. Pol. Ecol. Stud. 3, 15–17 (1977)
Miquel, M., Bédard, Y., Brisebois, A., Pouliot, J., Marchand, P., Brodeur, J.: Modeling multi-dimensional spatio-temporal data werehouses in a context of evolving specifications. Int. Arch. Photogrammetry Remote Sens. Spat. Inf. Sci. 34, 142–147 (2002)
Lenz, H.J., Thalheim, B.: A formal framework of aggregation for the OLAP-OLTP model. J. Univ. Comput. Sci. 15, 273–303 (2009)
Briand, L.C., Morasca, S., Basili, V.R.: An operational process for goal-driven definition of measures. IEEE Trans. Softw. Eng. 28, 1106–1125 (2002)
Acknowledgements
Data acquisition received financial support from the FEDER Loire, Etablissement Public Loire, DREAL de Bassin Centre, the Région Bourgogne (PARI, Projet Agrale 5) and the French Ministry of Agriculture. We also thank heartily Pr. John Aldo Lee, from the Catholic University of Leuven, for his help.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Sautot, L., Bimonte, S., Journaux, L., Faivre, B. (2015). Dimension Enrichment with Factual Data During the Design of Multidimensional Models: Application to Bird Biodiversity. In: Hammoudi, S., Maciaszek, L., Teniente, E., Camp, O., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2015. Lecture Notes in Business Information Processing, vol 241. Springer, Cham. https://doi.org/10.1007/978-3-319-29133-8_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-29133-8_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-29132-1
Online ISBN: 978-3-319-29133-8
eBook Packages: Computer ScienceComputer Science (R0)