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The volume and complexity of Biomedical Imaging (BMI) data can be handled by well-known Product Lifecycle Management (PLM) solutions if a research study in this field is modeled as a cyclic process of four phases: study specifications; raw data acquisition; data processing and results publication. However, current PLM systems do not provide easy, flexible and user-adapted data access, especially in the context of heterogeneity expertise environments such as BMI. This paper presents VAQUEROdoi:10.14733/cadaps.2020.274-287 fatcat:f52yyp5eczcfnpxveuzfdck6vq