The Mobius Project, OSU Department of Biomedical Informatics, Multiscale Computing Laboratory

Abstract: Advances in computational resources, the concept of the Grid and the development of middleware and applications to build and support the Grid will give Grid users the power to access and interpret large amounts of heterogeneous data. Metadata, data that describes data, can be used to represent and define the protocols of the Grid, as an abstraction between services and datasets, and to provide syntactic or semantic descriptions and annotations of any sized datasets so that they may be discovered, communicated, and analyzed efficiently. In this document, we will present Mobius, which can be described as a generic and extensible set of protocols and services for managing data in a Grid environment.

Abstract: Images are a common data type in many different aspects of science and medicine. Images are used in analysis from oil resevoir production quantification to lung cancer diagnosis. Information can be abstracted from images in many ways using a wide variety of analysis techniques. As non-invasive data collection technology grows in many different areas we begin to see more and more image acquisition techniques yielding more and more image data at higher resolutions. Managing this data efficiently is not only a large and complex problem but a problem where, if solved efficiently, yields critical new findings. Image storage, querying, and retrieval is a critical component to enable the use image data in a scientific setting. From doctors in hospitals to research scientists in their fields, effi- cient management of large quantities of ever growing sizes of image data help lead them to there finding faster saving them time and money while advancing there fields. In this paper we present a distributed framework for managing images in a massive scale, leveraging new advances in grid middleware coupled with large interconnected computation and storage hardware.