The growth of multi-level modeling has resulted in an increase of level-organization alternatives which significantly differ from each other with respect to their underlying foundations and the well-formedness rules they enforce. Alternatives substantially diverge with respect to how level boundaries should govern instance-of relationships, what modeling mechanisms they employ, and what modeling principles they establish. In this article, I analyze how a number of multi-level modeling approaches deal with certain advanced modeling scenarios. In particular, I identify linear domain metamodeling, i.e., the requirement that all domain-induced instance-of relationships align with a single global level-hierarchy, as a source of accidental complexity. I propose a novel multi-dimensional multi-level modeling approach based on the notion of orthogonal ontological classification that supports modeling of domain scenarios with minimal complexity while supporting separation of concerns and sanity-checking to avoid inconsistent modeling choices.