What is it about?
Multiple levels of classification naturally occur in many domains. Several modeling approaches account for this and a subset of them attempt to provide their users with sanity-checking mechanisms in order to guard them against conceptually ill-formed models. We formalized and implemented multi-dimensional multi-level modeling, an approach that supports sanity-checking without imposing limitations on its users.
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Why is it important?
Model well-formedness is important. Modeling mistakes are easily made and models need to be reliable sources of information. The approach we formalized and implemented is capable of detecting many model inconsistencies automatically.
Perspectives
We hope that the ideas presented and the techniques used will find adoption beyond this particular effort.
Thomas Kuehne
Victoria University of Wellington
Read the Original
This page is a summary of: Supporting Sound Multi-Level Modeling—Specification and Implementation of a Multi-Dimensional Modeling Approach, Data & Knowledge Engineering, November 2025, Elsevier,
DOI: 10.1016/j.datak.2025.102481.
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