Constructing the integral OLAP-Model for scientific activities based on FCA

  • Authors:

  • Tatiana Penkova;Anna Korobko

  • Affiliations:

  • Institute of Computational Modeling of the Siberian Branch, Russian Academy of Science, Krasnoyarsk, Russia;Institute of Computational Modeling of the Siberian Branch, Russian Academy of Science, Krasnoyarsk, Russia

  • Venue:
  • KES'12 Proceedings of the 16th international conference on Knowledge Engineering, Machine Learning and Lattice Computing with Applications
  • Year:
  • 2012

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Abstract

In this paper an original approach to analytical decision making support based on on-line analytical processing of multidimensional data is suggested. According to Dr. Codd's rules, the effectiveness of data analysis significantly depends on the data accessibility and transparency of an analytical model of domain. The method of constructing a conceptual OLAP-model as an integral analytical model of the domain is proposed. The method is illustrated by the example of the scientific activities domain. The integral analytical model includes all possible combinations of analyzed objects and gives them the opportunity to be manipulated ad-hoc. The suggested method consists in a formal concept analysis of measures and dimensions based on an expert knowledge about the structure of analyzing objects and their comparability. As a result, conceptual OLAP-model is represented as a concept lattice of multidimensional cubes. Concept lattice features allow the decision maker to discover the nonstandard analytical dependencies on the set of all actual measures and dimensions of the scientific activities domain. Conceptual OLAP-model implementation allows user makes better decisions based on on-line analytical processing of the scientific activity indicators.