Abstract
Performance indicators are calculated by composition of more basic pieces of information, and/or aggregated along a number of different dimensions. The multidimensional model is not able to take into account the compound nature of an indicator. In this work, we propose a semantic multidimensional model in which indicators are formally described together with the mathematical formulas needed for their computation. By exploiting the formal representation of formulas an extended drill-down operator is defined, which is capable to expand an indicator into its components, enabling a novel mode of data exploration. Effectiveness and efficiency are briefly discussed on a prototype introduced as a proof-of concept.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Kaplan, R.S., Norton, D.P.: The Balanced Scorecard: Measures that Drive Performance. Harvard Business Review 70, 71–79 (1992)
Popova, V., Sharpanskykh, A.: Modeling organizational performance indicators. Information Systems 35, 505–527 (2010)
Ackoff, R.L.: Management misinformation systems. Management Science 14 (1967)
Lakshmanan, L.V.S., Pei, J., Zhao, Y.: Efficacious data cube exploration by semantic summarization and compression. In: VLDB, pp. 1125–1128 (2003)
Neumayr, B., Anderlik, S., Schrefl, M.: Towards Ontology-based OLAP: Datalog-based Reasoning over Multidimensional Ontologies. In: Proc. of the Fifteenth International Workshop on Data Warehousing and OLAP, pp. 41–48 (2012)
Niemi, T., Toivonen, S., Niinimäki, M., Nummenmaa, J.: Ontologies with semantic web/grid in data integration for olap. Int. J. Sem. Web Inf. Syst. 3, 25–49 (2007)
Huang, S.M., Chou, T.H., Seng, J.L.: Data warehouse enhancement: A semantic cube model approach. Information Sciences 177, 2238–2254 (2007)
Priebe, T., Pernul, G.: Ontology-Based Integration of OLAP and Information Retrieval. In: Proc. of DEXA Workshops, pp. 610–614 (2003)
Pedrinaci, C., Domingue, J.: Ontology-based metrics computation for business process analysis. In: Proc. of the 4th International Workshop on Semantic Business Process Management, pp. 43–50 (2009)
Xie, G., Yang, Y., Liu, S., Qiu, Z., Pan, Y., Zhou, X.: EIAW: Towards a Business-Friendly Data Warehouse Using Semantic Web Technologies. In: Aberer, K., et al. (eds.) ISWC/ASWC 2007. LNCS, vol. 4825, pp. 857–870. Springer, Heidelberg (2007)
Kehlenbeck, M., Breitner, M.H.: Ontology-based exchange and immediate application of business calculation definitions for online analytical processing. In: Pedersen, T.B., Mohania, M.K., Tjoa, A.M. (eds.) DaWaK 2009. LNCS, vol. 5691, pp. 298–311. Springer, Heidelberg (2009)
Golfarelli, M., Mandreoli, F., Penzo, W., Rizzi, S., Turricchia, E.: OLAP Query Reformulation in Peer-to-peer Data Warehousing. Inf. Sys. 37, 393–411 (2012)
Horkoff, J., Barone, D., Jiang, L., Yu, E., Amyot, D., Borgida, A., Mylopoulos, J.: Strategic business modeling: representation and reasoning. Software & Systems Modeling (2012)
del-Río-Ortega, A., Resinas, M., Ruiz-Cortés, A.: Defining process performance indicators: An ontological approach. In: Meersman, R., Dillon, T.S., Herrero, P. (eds.) OTM 2010. LNCS, vol. 6426, pp. 555–572. Springer, Heidelberg (2010)
Diamantini, C., Potena, D.: Semantic enrichment of strategic datacubes. In: Proc. of the ACM 11th International Workshop on Data Warehousing and OLAP, DOLAP 2008, pp. 81–88 (2008)
Chesbrough, H.: Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business Press, Boston (2003)
Gray, J., Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M., Pellow, F., Pirahesh, H.: Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Data Min. Knowl. Discov. 1, 29–53 (1997)
Neumayr, B., Schrefl, M.: Multi-level conceptual modeling and OWL. In: Heuser, C.A., Pernul, G. (eds.) ER 2009. LNCS, vol. 5833, pp. 189–199. Springer, Heidelberg (2009)
Diamantini, C., Potena, D., Storti, E.: A logic-based formalization of KPIs for virtual enterprises. In: Franch, X., Soffer, P. (eds.) CAiSE Workshops 2013. LNBIP, vol. 148, pp. 274–285. Springer, Heidelberg (2013)
Diamantini, C., Potena, D., Proietti, M., Smith, F., Storti, E., Taglino, F.: A semantic framework for knowledge management in virtual innovation factories. International Journal of Information System Modeling and Design 4, 70–92 (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Diamantini, C., Potena, D., Storti, E. (2014). Extending Drill-Down through Semantic Reasoning on Indicator Formulas. In: Bellatreche, L., Mohania, M.K. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2014. Lecture Notes in Computer Science, vol 8646. Springer, Cham. https://doi.org/10.1007/978-3-319-10160-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-10160-6_6
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10159-0
Online ISBN: 978-3-319-10160-6
eBook Packages: Computer ScienceComputer Science (R0)