We study (unions of) conjunctive metaqueries over ontologies expressed in the Description Logics counterpart of RDFS equipped with metamodeling capabilities. This generalization to metaquerying goes beyond the extensively investigated query answering problem over ontologies, as now queries may also contain metavariables and TBox atoms, aligning with the classical “Ask-and-Tell” paradigm in knowledge representation. For the semantics of queries, we adopt the \(\texttt {SPARQL} \) Metamodeling Semantics Entailment Regime, a recently introduced regime that generalizes the commonly used \(\texttt {SPARQL} \) Direct Semantics Entailment Regime by relaxing the typing constraints. This new regime supports a more flexible querying mechanism over ontologies involving metaclasses and metaproperties, as query variables can appear in positions of different types (i.e. as individual, class, or property). As a result, it enables the formulation of meaningful metaqueries related to metamodeling. We show that this query answering task can be reduced to the evaluation of a linear Datalog program. This Datalog encoding allows us to establish tight complexity bounds for the associated decision problem, in combined complexity, ontology complexity and data complexity.