Abstract
Legal information retrieval in civil law systems faces challenges such as the diversity of legislative structures, the complexity of conceptual relations, and the limitations of keyword based search. Legal ontologies, by providing structured models for representing concepts, rules, and relations, enable a shift from surface level keyword retrieval to semantic retrieval. Using a systematic review and interpretive synthesis within the Context–Mechanism–Outcome (CMO) framework, this study addresses four core questions: the contextual factors influencing the design of legal ontologies, the mechanisms that enhance semantic retrieval, the dominant technical approaches and design challenges in civil law systems, and an appropriate conceptual framework for developing localized models in Iran. A comprehensive search across major international and national databases retrieved 923 records; after screening, 28 studies met the criteria for final analysis. The findings show that design orientation is shaped by the legal context; effective mechanisms include hybrid methodologies, automated approaches, and the use of upper ontologies; and the dominant technical model—based on Web Ontology Languages—has the capacity to adapt to civil law systems such as Iran. Although some ontology based systems in highly regulated domains have achieved accuracies above 0.98, the lack of context sensitive design and the gap between legal theory and ontology engineering remain major challenges. Based on the analysis, the LKIF framework is one of the reference models in international studies, but its application in the Persian–legal context requires redesign, localization, and empirical evaluation. By proposing a localized conceptual framework, this study paves the way for developing semantic infrastructures and achieving precise, reliable, and context aligned legal information retrieval in Iran’s legal system.