Explorations into the Provenance of High Throughput Biomedical Experiments James P. McCusker and Deborah L. McGuinness Tetherless World Constellation Department of Computer Science Rensselaer Polytechnic Institute 110 8th Street Troy, NY 12180, USA {mccusj,dlm}@cs.rpi.edu http://tw.rpi.edu Abstract. The field of translational biomedical informatics seeks to in- tegrate knowledge from basic science, directed research into diseases, and clinical insights into a form that can be used to discover effective treat- ments of diseases. We demonstrate methods and tools to generate RDF representations of a commonly used experimental description format, MAGE-TAB, mappings of MAGE documents to two general-purpose provenance representations, OPM (Open Provenance Model) and PML (Proof Markup Language). We show through a use case simulation that the data represented in MAGE documents can be completely represented in OPM and PML through use of round trip analysis of certain exam- ples. The success in mapping MAGE documents into general-purpose provenance models shows that promise in the implementation of the translational research provenance vision. 1 Introduction Translational biomedical research focuses on translating findings in basic science into advances in treatment and diagnosis of diseases for patients in the clinic, and has become a major research priority in the last five years. [1,2] Translational research requires the coordination and collaboration of a number of different disciplines, including basic science, clinical research, and increasingly, biomedi- cal informatics. [3] As the scale and complexity of biomedical experiments has increased, so has the role of biomedical informatics. It plays an active role in the design, execution, and analysis of most biomedical research. The translational research pipeline, often thought of as a cycle of knowledge from the experimental “bench” to the clinical “bedside” and back, requires the management of many different kinds of data and artifacts by specialists in their disciplines. This in- cludes information about the collection, management, and disposition of human, animal, and xenographic biomaterials, collection and management of partici- pants in clinical research and trials, management of patient histories and charts, data from lab results, diagnostic imaging at the radiological and histopatholog- ical scales, as well as experiments using high-throughput technologies such as D.L. McGuinness, J.R. Michaelis, and L. Moreau (Eds.): IPAW 2010, LNCS 6378, pp. 120–128, 2010. c  Springer-Verlag Berlin Heidelberg 2010