Traditional SPARQL provenance has focused on explainability, while data sharing today increasingly requires privacy preservation and cryptographic verification. We thus introduce zkRDF, a data-centric approach that enables a data holder (the prover) to guarantee soundness of SPARQL query results to a data consumer (the verifier) while exposing only the minimal information needed for the proof. Unlike existing methods that prove query execution, we establish soundness of query results by proving properties about the queried RDF dataset. Given a consumer’s query, the holder materializes a selectively disclosing view of the queried dataset, revealing required information and cryptographically hiding the remainder. Zero-Knowledge Proofs (ZKPs) guarantee both the integrity of the derived dataset and the adherence of hidden elements to desired constraints, such as numeric bounds. The consumer verifies the proofs and obtains the desired query results from the dataset. Importantly, proof verification ensures dataset validity and, therefore, guarantees sound query results. We present zkRDF’s methodology, detail the interpretation of SPARQL queries to produce sound results, and prove soundness of our approach. We discuss zkRDF’s support for SPARQL features and show that our proof-of-concept implementation outperforms an approach that proves query execution by three orders of magnitude.