Modern, molecular bio-medicine is driving a growing demand for extensively annotated tissue bank specimens. With careful clinical, pathologic and outcomes annotation, samples can be better matched to the research question at hand and experimental results better understood and verified. However, the difficulty and expense of detailed specimen annotation is well beyond the capability of most banks and has made access to well documented tissue a major limitation in medical research. In this context, we have implemented automated annotation of banked tissue by integrating data from three clinical systems – the cancer registry, the pathology LIS and the tissue bank inventory system - through a classical data warehouse environment. The project required modification of clinical systems, development of methods to identify patients between and map data elements across systems and the creation of de-identified data in data marts for use by researchers. The result has been much more extensive and accurate initial tissue annotation with less effort in the tissue bank, as well as dynamic ongoing annotation as the cancer registry follows patients over time.