Snezana, Savoska and Suzana, Loshkovska (2026) An Ontological Framework for Multidimensional and Multivariate Data Visualization with Applications to Financial and Accounting Data. Informatics, 13 (8). ISSN 2227-9709
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Abstract
Selecting an appropriate visualization technique for multidimensional and multivariate finan
cial and accounting (F&A) data remains a complex, user-dependent task. The TaxUI&BV4FADA
taxonomypreviouslyorganizedthisproblemalongfourdimensions—visualizationtechniques,
user intentions and analytical goals, interaction possibilities, and user groups—but as a human
readable structure, it could not be queried, validated, or integrated into semantic decision
support pipelines. This paper presents an ontological framework that extends TaxUI&BV4FADA
into a machine-readable OWL DL artifact authored in WebProtégé, with OWL used for seman
tic structuring and SPARQL used for score-based recommendation retrieval. The framework
formalizes the four taxonomy dimensions and adds a decision-support layer and an evalu
ation layer. An explicit F&A semantic mapping is provided, and two contrasting worked
scenarios—a financial analyst testing a gross-margin hypothesis and a CFO seeking a quar
terly overview—show that the framework discriminates between F&A roles and analytical
tasks. The evaluation demonstrates logical consistency, competency-question satisfaction,
and internal consistency of the populated recommendation matrix against taxonomy
derived expectations, rather than independent empirical recommendation accuracy. This
constitutes an internal, artifact-centered validation rather than an external empirical study
with end users, and a protocol for future empirical validation with financial and accounting
professionals is outlined. The framework provides a domain-oriented semantic and matrix
based decision-support foundation on which executable F&A visualization recommenders
can be built.
| Item Type: | Article |
|---|---|
| Subjects: | Scientific Fields (Frascati) > Natural sciences > Computer and information sciences |
| Divisions: | Faculty of Information and Communication Technologies |
| Depositing User: | Prof. d-r. Andrijana Bocevska |
| Date Deposited: | 09 Sep 2026 16:32 |
| Last Modified: | 09 Sep 2026 16:32 |
| URI: | https://eprints.uklo.edu.mk/id/eprint/11751 |
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