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Legacy systems are usually made of two kind of artifacts: source code and databases. Typically, the maintenance of those systems is carried out through re-engineering processes. Although both artifacts can be independently maintained, for a more effective re-engineering of the whole system both should be analyzed and evolved jointly. This is mainly due to the fact that the knowledge expected to be extracted by analyzing both kind of artifacts at the same time is greater and richer than the one recovered by just looking at the system partly, and thus ROI and lifespan of the system are expected to improve. This paper proposes the data contextualization for recovering code-to-data linkages in legacy systems. This technique is framed in the ADM (architecture driven modernization) approach to modernization of legacy systems, considering all involved artifacts as models. This paper also presents a tool to support that technique throughout a real-life case study.